Focused Photonics (China)

In multimessenger high-energy astrophysics, interpreting observed spectra often hinges on understanding the underlying competition between energy gains and radiative losses within the accelerator. To progress along these lines, we report here on numerical particle-in-cell simulations of particle acceleration in relativistic, magnetized turbulent pair plasmas including synchrotron radiative losses. We investigate a regime of weak synchrotron cooling, where the maximal energy predicted by balancing the acceleration and radiation rates resides in the suprathermal tail, i.e., above the thermal bulk and below the confinement energy associated with the outer scale of the turbulence. Our key finding is that the particle energy spectrum, along with the radiated synchrotron spectral power, does not terminate at this maximal energy (or corresponding frequency), but extends significantly beyond with a steepened spectrum, up to the synchrotron burn-off limit where particles cool within a gyrotime. For our adopted parameters (turbulence magnetization parameter $\ensuremath{\sigma}\ensuremath{\approx}1$ and amplitude $\ensuremath{\delta}B/{B}_{0}\ensuremath{\simeq}1$), the particle distribution function follows $\mathrm{d}n/\mathrm{d}\ensuremath{\gamma}\ensuremath{\propto}{\ensuremath{\gamma}}^{\ensuremath{-}s}$ with $s\ensuremath{\simeq}3$ below the predicted maximal energy, then steepens to $s\ensuremath{\simeq}4$ above. The particle energy distribution and the radiated synchrotron spectra display strong variability near the cutoff energy down to timescales well below the largest eddy turn-around time. We substantiate our results by demonstrating that the acceleration rate itself displays a broken power-law-like distribution, whose mean value defines the diffusion coefficient and whose maximal value is the gyrofrequency. We perform a detailed analysis of the acceleration mechanism for the highest-energy particles and demonstrate that they are accelerated to this extreme limit by a generalized Fermi process in ideal electric fields. This process is driven by a gradient of the four-velocity field ${u}_{E}$ of the magnetic field lines of relativistic amplitude, $\ensuremath{\delta}{u}_{E}\ensuremath{\gtrsim}c$, ordered on a scale comparable to, or larger than, the particle gyroradius at the synchrotron burn-off limit. We contend that this is a generic feature of relativistic, large-amplitude turbulence. Finally, we apply our results to the case of the Crab nebula, which exhibits a hierarchy of characteristic Lorentz factors similar to that studied here. We conclude that stochastic acceleration in this environment is a promising mechanism for explaining the highest-energy part of the synchrotron spectral energy distribution and its variability.

In “Saving Societies From Within: Innovation and Equity Through Inter-Organizational Networks,” authors Lawrence Brown and Bradford Hesse present a compelling vision for leveraging inter-organizational networks to transform how societies address complex public challenges, particularly in the areas of health and equity. This book review explores the authors’ central proposition – the Sustainable, Cooperative, Inclusive, Organized Network (SCION) model – as a scalable framework that transcends traditional silos in public service delivery. Drawing from real-world examples and grounded in action theory, the book offers both a diagnostic lens for understanding systemic fragmentation and a prescriptive strategy for reimagining networked governance. Brown and Hesse emphasize translational health as a keystone for collective impact, proposing that societal coordination failures can be addressed through deliberately designed, relationship-centered institutions. This review examines the clarity and practicality of the SCION model, highlighting its relevance to public health, education, and civic infrastructure, while also acknowledging the challenges of implementation in politically fragmented environments. Ultimately, the book makes a timely and actionable contribution to the fields of public administration and health policy, advocating for a relational and inclusive approach to organizing for the public good.

Abstract Density dependence, both conspecific and heterospecific, is widely recognized as a crucial driver of plant species diversity. However, treating multiple heterospecific species as a homogeneous group obviously overlooks the variability in the impacts of different heterospecific neighbors on the survival or growth of focal species. In this study, we developed the Static-Dynamic Coupled Interspecific Association Classification Framework (SDIACF), which categorizes heterospecific neighbors based on their positive/negative interspecific associations and dynamic changes with focal species. We further used generalized linear mixed-effect models to analyze how conspecific and various heterospecific neighbors classified by the above framework influenced the survival and growth rates of the focal species. Our results revealed that heterospecific neighbors, deconstructed using SDIACF, exerted distinct effects on the focal species. Specifically, regardless of their initial interspecific association with the focal species, heterospecific neighbors with more negative associations showed a negative impact on the focal species, while those with more positive associations showed a positive effect. However, among heterospecific neighbors exhibiting identical dynamic interspecific associations, positively associated neighbors were slightly more conducive to the survival of the focal species than negatively associated ones, but slightly detrimental to its growth. In summary, our results demonstrate that heterospecific neighbors are not a homogeneous entity but play important and complex roles in species coexistence. The development of SDIACF not only constitutes a significant supplement to traditional density dependence research but also offers a novel perspective for further exploring species coexistence.

Using a laser to produce energy from fusion has been a grand challenge since shortly after the laser was invented. Historic advances in inertial fusion have been made in the past few years on the National Ignition Facility (NIF) laser. First was a “burning plasma” - where the plasma heating by fusion alpha particle deposition became the dominant source of heating. Shortly after, the first experiment to achieve ignition, defined by the Lawson criterion, occurred. This experiment demonstrated the first plasma where alpha heating dominated over all loss mechanisms, producing strong heating of the plasma, and fusion “gain” (energy out divided by laser energy in) of 0.72. Lastly, fusion gain greater than 1 was achieved - fusion energy out more than 1.5 x the laser energy put into the target.

The creation of quaternary carbon centers has been a formidable challenge in organic synthesis due to steric impediments, especially for the polyaryl substituted quaternary carbon centers. Up to now, a few of methods were reported for achieving the α-arylation of 3-aryloxindoles to construct 3,3-diaryloxindoles. We now asserted the TfOH-catalyzed cross-dehydrogenative coupling reaction between the tertiary C(sp3)-H and readily available arenes under air atmosphere in green reaction medium for rapid construction of 3,3-diaryloxindoles. In addition, the mechanism of the metal-free cross-dehydrogenative coupling with air as oxidant was meticulously explored.

In this study, we developed ashless cellulose filter papers as calibration standards in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to rapidly determine multi-element concentrations in airborne fine particulate matter (PM2.5). To achieve this, the papers were treated by immersion in standard solutions, followed by evaporation of the solutions. The homogeneity of the paper standards was studied, and the results demonstrated that the elements were homogeneously distributed at the paper centers with slight fluctuations (i.e., relative standard derivation ≦ 8%). The instrument signal drift and instability were compensated using a pseudo internal standard (197Au). The limits of detection established for LA-ICP-MS were obtained by the ablation of 11 lines on the procedural blank filter paper containing 0.5% HNO3, with values ranging from 0.01 (Sr) to 0.49 μg g−1 (Fe). The accuracy of the LA-ICP-MS determinations was validated using certified reference materials (CRMs) and analyzed using six line scans. The results showed acceptable analytical errors (<13%). Thus, our method was applied to analyze actual PM2.5 samples. Moreover, the sources of PM2.5 in Hangzhou were also investigated. Additionally, this method has considerable potential for multi-element analysis in other airborne dusts.

In order to improve the stability of extreme learning machine (ELM), it was proposed to use the combination of robust independent component analysis (RobustICA) and particle swarm optimization ELM algorithm. It was applied to identify the maturity of cuiguan pear at different growing periods. First the two order derivative and the discrete wavelet transform were adopted to remove the background noise and compression spectra. Then RobustICA was used to decompose the spectra to extract independent components and mixed coefficient matrices. Finally, by using particle swarm optimization, the best input layer weight and hidden layer deviation were obtained and adjusted the number of hidden layer nodes to get the best ELM model to differentiate maturity. The method was used to identify the maturity of cuiguan pear at four different stages, and has strong robustness. The results showed that RobustICA-PSO-ELM had better discrimination ability compared with RobustICA - ELM and ELM, and the accuracy increases from 75% to 94.4%.

In this study, long term measurements of PM_(2.5) and ultrafine particles (UFPs) for daily average mass concentration at Zhongshan (ZS), Sinjhuang (SJ), and Jhudong (JD) urban air monitoring stations were conducted from 2011 spring to 2013 autumn. The results showed that daily average UFPs mass concentrations in spring (average at 3 stations: 1.58 ± 0.74 μg m^(-3)) and summer (average at 3 stations: 1.59±0.53 μg m^(-3)) were higher than those in autumn (average at 3 stations: 1.02±0.28 μg m^(-3)) and winter (average at 3 stations: 1.04±0.48 μg m^(-3)) due to the impacts by heavy traffic emission and new particle formation event. The effective density (ρ_(eff)) and dynamic shape factor (χ) for ultrafine particles (UFPs) were found to be 0.68±0.16 g cm^(-3) and 2.06 ± 0.19, respectively, suggesting that the particle morphology was irregular shape. Based on the calculated ρ_(eff) and χ, the average number and surface area concentration ratio of UFPs to those of PM_(2.5) at these monitoring stations was determined to be 89.0±5.5% and 42.1±12.8%, respectively, suggesting that UFPs contribute significantly to the health-relevant PM_(2.5) aerosol fraction in these stations.

Aerosol pollution episodes have frequently occurred in China in recent years, and the airborne trace elements in particulate matter have been a cause for concern worldwide because of their impacts on human health. However, there is limited information on the hourly variations of airborne trace elements. This paper describes a detailed investigation conducted in March 2013 on the hourly variations and potential sources of airborne trace elements. Trace elements in particles with aerodynamic diameters less than 10 μm (PM_(10)) were monitored on-line in four representative regions with similar latitudes in southeastern China. Our results showed that the number of species of elements in PM_(10) detected at urban sites and an industrial park was greater than that at a rural site, due to the influences of human activities. The hourly variation patterns of trace elements indicated that their concentrations were stable during the day at the rural site, whereas a visible ＂double peak＂ of Pb and Cu was observed in the tourist city and a ＂single morning peak＂ of Pb and As was seen in the industrial city. These variations indicated the abundant traffic in the tourist city, and strong industrial emissions in the industrial city. However, the single morning peak and the slight double peak patterns of the trace elements were both found at the industrial park, indicating a combined source of industry and traffic. The results from the source identification also indicated that the sources of airborne elements were mainly industrial emissions at industrial sites, whereas the elements in the tourist city might primarily result from traffic. The correlations between PM_(10) concentrations and trace element concentrations were also studied. The results revealed that PM_(10) correlated better with elements originating from natural sources (e.g., K, Ca, Fe) than with those from anthropogenic sources (e.g., Pb, Zn, Cu). Our results provide a scientific basis for pollution control strategies at these sites.