Miracle-dz/UniFAR-FTUs huggingface dataset:
Climate change reduces resilience to fire in subalpine rainforests

Climate change is affecting the distribution of species and the functioning of ecosystems. For species that are slow growing and poorly dispersed, climate change can force a lag between the distributions of species and the geographic distributions of their climatic envelopes, exposing species to the risk of extinction. Climate also governs the resilience of species and ecosystems to disturbance, such as wildfire. Here we use species distribution modelling and palaeoecology to assess and test the impact of vegetation–climate disequilibrium on the resilience of an endangered fire‐sensitive rainforest community to fires. First, we modelled the probability of occurrence of Athrotaxis spp. and Nothofagus gunnii rainforest in Tasmania (hereon “montane rainforest”) as a function of climate. We then analysed three pollen and charcoal records spanning the last 7,500 cal year BP from within both high (n = 1) and low (n = 2) probability of occurrence areas. Our study indicates that climatic change between 3,000 and 4,000 cal year bp induced a disequilibrium between montane rainforests and climate that drove a loss of resilience of these communities. Current and future climate change are likely to shift the geographic distribution of the climatic envelopes of this plant community further, suggesting that current high‐resilience locations will face a reduction in resilience. Coupled with the forecast of increasing fire activity in southern temperate regions, this heralds a significant threat to this and other slow growing, poorly dispersed and fire sensitive forest systems that are common in the southern mid to high latitudes.
NF‐κB targeting for overcoming tumor resistance and normal tissues toxicity

Radiotherapy and chemotherapy are two famous modalities in tumor‐targeted therapy that lead to systemic and local toxicities for normal tissues. Moreover, several studies have confirmed that exposure of the tumor to radiation or chemotherapy drugs stimulate some signaling pathways in the tumor microenvironment (TME), leading to resistance of cancer cells to apoptosis, as well as promoting angiogenesis and tumor growth. Nuclear factor kappa B (NF‐κB) plays a central role in the regulation of inflammatory responses in both normal tissues and tumors via the release of several cytokines, regulation of prostaglandins, reduction/oxidation (redox) reactions, angiogenesis, and cell death. Upregulation of NF‐κB in normal tissues causes an appearance of inflammatory reactions and oxidative stress, whereas it regulates angiogenesis and suppresses apoptosis, leading to resistance to subsequent doses of radiation or chemotherapy. Selective inhibition of NF‐κB in experimental studies has shown promising results for tumor sensitization via apoptosis induction, inhibition of angiogenesis, and increasing delay of tumor growth. The use of some agents for NF‐κB inhibition has been shown to alleviate radiation/chemotherapy toxicities in normal cells/ tissues. In this current review, we explained the pivotal role of NF‐κB in both normal tissue toxicity and tumor resistance. We also discussed the promising strategies for overcoming these problems with regard to chemotherapy and radiotherapy.
Antihypertensive treatment for hypertensive patients with heart failure using real-world Japanese data: subanalysis of the Retrospective study of antihypertensives for lowering blood pressure (REAL) study

ABSTRACT The number of patients with heart failure (HF) is rapidly increasing. Although hypertension is related to onset of HF, antihypertensive treatment status for these patients has not been fully examined. We conducted a claims-based study to discern the treatment status of Japanese hypertensive patients with HF. Two Japanese databases (2008–2016) from acute care hospitals and health insurance societies were used to analyze prescription rates for antihypertensive drug class or category of diuretics in all hypertensive patients and the subset of patients with HF. Totals of hypertensive patients and those with HF in each database in 2015 were 4,191,666 and 1,404,008 patient-months, and 1,382,732 and 148,194 patient-months, respectively. In the acute care hospitals database, calcium channel blockers (CCBs) (55.0–56.5%) and angiotensin II receptor blockers (49.4–54.7%) were prescribed most. β-blockers (38.7–48.0%) and diuretics (42.3–45.6%) were prescribed more for hypertensive patients with HF than for all hypertensive patients (21.5–24.8% and 25.5–26.7%, respectively). Loop diuretics were also prescribed more often for hypertensive patients with HF (68.3–76.0% from acute care hospitals and 47.8–55.8% from health insurance societies) than for all hypertensive patients (56.7–61.7% and 16.4–18.3%). The size of medical institution had a greater effect on drug selection than patient age in both patient groups. Given recommendations in guidelines for hypertensive patients with HF, the differences in drug choice in comparison with all hypertensive patients appear reasonable. However, some deviations, such as the high rate of CCBs in frontline and preference for angiotensin II receptor blockers over angiotensin-converting enzyme inhibitors, did not appear to follow guidelines.
Numerical results for geometric measure of coherence and geometric measure of entanglement based on semidefinite programs

We present semidefinite programs for computing the geometric measure of coherence and the geometric measure of entanglement, respectively. For the geometric measure of coherence, the algorithm can be applied to any finite-dimensional mixed state. We test randomly generated single-qubit states, single-qutrit states, and a special kind of $d$-dimensional mixed states. For the geometric measure of entanglement, the algorithm is applied to all two-qubit and qubit-qutrit states, and some special kinds of higher dimensional mixed states. For other states, the algorithm can get a lower bound of the geometric measure of entanglement. Randomly generated two-qubit states, the isotropic states and the Werner states are tested. Furthermore, the maximum deviation between the analytical solution and the numerical solution is calculated.
Review of Unmanned Aerial Vehicle Swarm Communication Architectures and Routing Protocols

Over the past decades, Unmanned Air Vehicles (UAVs) have achieved outstanding performance in military, commercial and civilian applications. UAVs are increasingly appearing in the form of swarms or formations to meet higher mission requirements. Communication plays an important role in UAV swarm control and coordination. The communication architecture defines how information is exchanged between UAVs or between UAVs and the central control center. Routing protocols help provide reliable end-to-end data transmission. Therefore, it is particularly important to design UAV swarm communication architectures and routing protocols with high performance and stability. This review article details four communication architectures including the advantages and disadvantages. Applicable scenarios are also discussed. In addition, a systematic overview and feasibility research of routing protocols are presented in this paper. To spur further research, the open research issues of UAV swarm communication architectures and routing protocols are also investigated.
A Time-Split MacCormack Scheme for Two-Dimensional Nonlinear Reaction-Diffusion Equations

A three-level explicit time-split MacCormack scheme is proposed for solving the two-dimensional nonlinear reaction-diffusion equations. The computational cost is reduced thank to the splitting and the explicit MacCormack scheme. Under the well known condition of Courant-Friedrich-Lewy (CFL) for stability of explicit numerical schemes applied to linear parabolic partial differential equations, we prove the stability and convergence of the method in $L^{\infty}(0,T;L^{2})$-norm. A wide set of numerical evidences which provide the convergence rate of the new algorithm are presented and critically discussed.
Adoption of Artificial Intelligence for Diagnosis and Treatment of Staphylococcus aureus Infections Disease on Humans

The aim of this paper is to develop an expert system that could aid medical practitioner to effectively diagnose and treat Staphylococcus aureus infections disease on a human. The objective of the research includes to develop an expert system for quick diagnosis and detection of Staphylococcus aureus bacteria on human skin, a system that aids in accurate treatment of staph infectious diseases by doctors, helps in quick decision making in the hospital, improves accuracy in drug prescription, and a system that will bring about computerized storage process, and to enlighten the knowledge workers on how to implement a computer based decision support systems and importance of it in the health care. The research was motivated due to delay in diagnosis and identification of Staphylococcus aureus bacteria and the fast rate at which infectious disease is spreading, delay in treatment of these bacteria, increase of guess work by health practitioners leading to delay in decision making and lack of electronic storage facility in the hospitals. Top down approach was used in the system design of this research while adopting expert system as the methodology and the programming language used was Java and database design used was MySQL. The result after design was a computerized standalone application that assists health practitioners (Doctor’s) in quick identification, diagnosis, prescription and treatment of Staphylococcus aureus bacteria on human skin. The expert system will facilitate quick decision making in the clinic.
Persistent Coulomb Blockade Across the Metal-Insulator Transition in Nanoparticle Solids

Nanoparticle solar cells have low carrier mobility. Key causes of this low mobility include that (1) the nanoparticle solids are insulators; and (2) the Coulomb blockade. The insulating behavior can be overcome by driving the system across a Metal-Insulator Transition (MIT). However, the evolution of the Coulomb blockade across the MIT has not been analyzed. This paper focuses on the behavior of the Coulomb blockade by analyzing carrier transport in the insulating phase by our Hierarchical Nanoparticle Transport Simulator, and by Dynamical Mean-Field Theory in the metallic phase. Our unexpected result is that the Coulomb blockade persists across the MIT.
Prediction of small‐for‐gestational‐age neonates at 35–37 weeks' gestation: contribution of maternal factors and growth velocity between 32 and 36 weeks

To assess the additive value of fetal growth velocity between 32 and 36 weeks' gestation to the performance of ultrasonographic estimated fetal weight (EFW) at 35 + 0 to 36 + 6 weeks' gestation for prediction of delivery of a small‐for‐gestational‐age (SGA) neonate and adverse perinatal outcome.
A distributed collaborative trust service recommender system for secure cloud computing

A model for providing solutions to the security issue of the cloud computing environment is addressed in this article by proposing a distributed collaborative trust service recommender (DTSR) system. DTSRs are kept in a distributed manner spread over the clouds, and they are used to extract raw trust from different sources. This trust information is based on the feedback by cloud service user's observation about the adherence of a cloud service provider (CSP) to a service level agreement for the cloud‐based service provided. Using this trust data, the overall trust of CSPs is computed by using collaborative computation. The trust values are propagated among the distributed DTSRs in the network so that the trust values are available to everyone in the cloud environment. Experiments were conducted, which clearly shows that our proposed system is useful in providing a secure multicloud environment.
Learning Accurate, Comfortable and Human-like Driving

Autonomous vehicles are more likely to be accepted if they drive accurately, comfortably, but also similar to how human drivers would. This is especially true when autonomous and human-driven vehicles need to share the same road. The main research focus thus far, however, is still on improving driving accuracy only. This paper formalizes the three concerns with the aim of accurate, comfortable and human-like driving. Three contributions are made in this paper. First, numerical map data from HERE Technologies are employed for more accurate driving; a set of map features which are believed to be relevant to driving are engineered to navigate better. Second, the learning procedure is improved from a pointwise prediction to a sequence-based prediction and passengers' comfort measures are embedded into the learning algorithm. Finally, we take advantage of the advances in adversary learning to learn human-like driving; specifically, the standard L1 or L2 loss is augmented by an adversary loss which is based on a discriminator trained to distinguish between human driving and machine driving. Our model is trained and evaluated on the Drive360 dataset, which features 60 hours and 3000 km of real-world driving data. Extensive experiments show that our driving model is more accurate, more comfortable and behaves more like a human driver than previous methods. The resources of this work will be released on the project page.
Clathrin‐dependent endocytosis predominantly mediates protein absorption by fat body from the hemolymph in Bombyx mori

During insect larval–pupal metamorphosis, proteins in the hemolymph are absorbed by the fat body for the maintenance of intracellular homeostasis; however, the type of proteins and how these proteins are internalized into the fat body are unclear. In Bombyx mori, the developmental profiles of total proteins in the hemolymph and fat body showed that hemolymph‐decreased protein bands (55–100 kDa) were in accordance with those protein bands that increased in the fat body. Inhibition of clathrin‐dependent endocytosis predominantly blocked the transportation of 55–100 kDa proteins from the hemolymph into the fat body, which was further verified by RNA interference treatment of Bmclathrin. Six hexamerins were shown to comprise ∼90% of the total identified proteins in both the hemolymph and fat body by mass spectrum (MS) analysis. In addition, hemolymph‐specific proteins were mainly involved in material transportation, while fat body‐specific proteins particularly participated in metabolism. In this paper, four hexamerins were found for the first time, and potential proteins absorbed by the fat body from the hemolymph through clathrin‐dependent endocytosis were identified. This study sheds light on the protein absorption mechanism during insect metamorphosis.
Hydroquinone-Based Fabrication of Gold Nanorods with a High Aspect Ratio and LSPR Greater than 850 nm to Be Used as a Surface Plasmon Resonance Platform for Rapid Detection of Thiophanate Methyl

The use of gold nanorods (AuNRs) as surface-enhanced Raman scattering (SERS) substrates has gained much attraction due to their remarkably aspect-ratio-dependent plasmonic properties. In this report, we described the development of AuNRs with a high aspect ratio and longitudinal surface plasmon resonance (LSPR) >850 nm through a hydroquinone-based fabrication with minor modifications. The synthesis started with the reduction of chloroauric acid (HAuCl4) by sodium borohydride (NaBH4) to make gold nanoseeds from which AuNRs were grown with the aid of silver nitrate (AgNO3), HAuCl4, cetyltrimethylammonium bromide (CTAB), and hydroquinone (HQ). Scanning electron microscopy coupled with energy-dispersive X-ray (SEM-EDX), Transmission electron microscope (TEM), X-ray diffraction (XRD) and Ultra-violet-Visible spectroscopy (UV-Vis) were performed to study the shape, size, and structural and optical properties of AuNRs, respectively. The results showed that AuNRs with high aspect ratios (AR > 3) were single crystals with a heterogenous size distribution, and that the growth of Au nanoseeds into AuNRs took place along the [001] direction. AuNRs exhibited two plasmon resonance peaks at 520 nm and 903 nm, while gold nanoseeds had only a plasmon resonance peak at 521 nm. The as-synthesized AuNRs also showed SERS effects for thiophanate methyl, a broad-spectrum fungicide, with the limit of detection down to 5 mg/L of the fungicide. AuNR-coated glass can serve as a SERS-based sensing platform for rapid detection of thiophanate methyl with high sensitivity and reproducibility.
State and Parameter Estimation from Observed Signal Increments

The success of the ensemble Kalman filter has triggered a strong interest in expanding its scope beyond classical state estimation problems. In this paper, we focus on continuous-time data assimilation where the model and measurement errors are correlated and both states and parameters need to be identified. Such scenarios arise from noisy and partial observations of Lagrangian particles which move under a stochastic velocity field involving unknown parameters. We take an appropriate class of McKean–Vlasov equations as the starting point to derive ensemble Kalman–Bucy filter algorithms for combined state and parameter estimation. We demonstrate their performance through a series of increasingly complex multi-scale model systems.
Evolution inclusions with time-dependent maximal monotone operators

This article studies the solutions of time-dependent differential inclusions which is motivated by their utility in the modeling of certain physical systems. The differential inclusion is described by a time-dependent set-valued mapping having the property that, for a given time instant, the set-valued mapping describes a maximal monotone operator. Under certain mild assumptions on the regularity with respect to the time argument, we construct a sequence of functions parameterized by the sampling time that corresponds to the discretization of the continuous-time system. Using appropriate tools from functional and variational analysis, this sequence is then shown to converge to the unique solution of the original differential inclusion. The result is applied to develop conditions for well-posedness of differential equations interconnected with nonsmooth time-dependent complementarity relations, using passivity of underlying dynamics (equivalently expressed in terms of linear matrix inequalities).
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling

In this comment on "Solving Statistical Mechanics Using Variational Autoregressive Networks" by Wu et al., we propose a subtle yet powerful modification of their approach. We show that the inherent sampling error of their method can be corrected by using neural network-based MCMC or importance sampling which leads to asymptotically unbiased estimators for physical quantities. This modification is possible due to a singular property of VANs, namely that they provide the exact sample probability. With these modifications, we believe that their method could have a substantially greater impact on various important fields of physics, including strongly-interacting field theories and statistical physics.
The Young and Nearby Normal Type Ia Supernova 2018gv: UV-optical Observations and the Earliest Spectropolarimetry

The nondetection of companion stars in SN Ia progenitor systems lends support to the notion of double-degenerate systems and explosions triggered by the merging of two white dwarfs. This very asymmetric process should lead to a conspicuous polarimetric signature. By contrast, observations consistently find very low continuum polarization as the signatures from the explosion process largely dominate over the pre-explosion configuration within several days. Critical information about the interaction of the ejecta with a companion and any circumstellar matter is encoded in the early polarization spectra. In this study, we obtain spectropolarimetry of SN 2018gv with the ESO Very Large Telescope at −13.6 days relative to the B-band maximum light, or ∼5 days after the estimated explosion—the earliest spectropolarimetric observations to date of any SN Ia. These early observations still show a low continuum polarization (≲0.2%) and moderate line polarization (0.30% ± 0.04% for the prominent Si ii λ6355 feature and 0.85% ± 0.04% for the high-velocity Ca component). The high degree of spherical symmetry implied by the low-line and continuum polarization at this early epoch is consistent with explosion models of delayed detonations and is inconsistent with the merger-induced explosion scenario. The dense UV and optical photometry and optical spectroscopy within the first ∼100 days after the maximum light indicate that SN 2018gv is a normal SN Ia with similar spectrophotometric behavior to SN 2011fe.
Obstetric intra‐operative cell salvage: a review of an established cell salvage service with 1170 re‐infused cases

The use of cell salvage during caesarean section has been increasing steadily, although there are concerns relating to cost, a perceived risk of amniotic fluid embolism, and fetal red cell sensitisation. We present observational data from almost a decade of use of intra‐operative cell salvage in obstetrics. By the end of this period, we set up cell salvage collection for > 98% of all caesarean sections. From 2008 to 2017, 1170 women have had a re‐infusion of cell salvaged blood with no clinical safety concerns; the median (IQR [range]) volume was 231 (154–306 [80–1690]) ml. During this time there has been a marked reduction in the number of women who were transfused allogeneic blood, as well as the amount of blood transfused. In total, 647 (55%) women have had alloimmunisation testing, with two positive cases. Quality control data indicate that the quality of blood processed from partial first bowls is no worse than that from full bowls. We discuss the costs of providing this service with regard to: staffing costs; single suction; leucodepletion filters; selectivity in the processing of collected blood; and the use of partial first bowls.
The Spillover Effect of Recreational Marijuana Legalization on Crime: Evidence From Neighboring States of Colorado and Washington State

An ongoing debate exists about the implications of recreational marijuana legalization to public safety. One important public concern is how recreational marijuana legalization may affect crime in neighboring states that have not legalized. Based on Uniform Crime Report (UCR) data from 2003 to 2017, this study used difference-in-differences (DID) analysis to examine the potential spillover effect of recreational marijuana legalization in Colorado and Washington State, with a special focus on the examination of the changes in the rates of a variety of crimes in the border counties of neighboring states relative to the nonborder counties in these states following Colorado’s and Washington’s legalization. Results provide some evidence suggesting a spillover crime reduction effect of legalization, as reflected by the significant decreases in the rates of property crime, larceny, and simple assault in the Colorado region that includes six neighboring states. Results also suggest that the effects of marijuana legalization on crime in neighboring states vary based on crime type and state.