Showing papers by "University of Arkansas published in 2018"

Classifying drivers of global forest loss

Abstract: Global maps of forest loss depict the scale and magnitude of forest disturbance, yet companies, governments, and nongovernmental organizations need to distinguish permanent conversion (ie, deforestation) from temporary loss from forestry or wildfire Using satellite imagery, we developed a forest loss classification model to determine a spatial attribution of forest disturbance to the dominant drivers of land cover and land use change over the period 2001 to 2015 Our results indicate that 27% of global forest loss can be attributed to deforestation through permanent land use change for commodity production The remaining areas maintained the same land use over 15 years; in those areas, loss was attributed to forestry (26%), shifting agriculture (24%), and wildfire (23%) Despite corporate commitments, the rate of commodity-driven deforestation has not declined To end deforestation, companies must eliminate 5 million hectares of conversion from supply chains each year

Catalysts for nitrogen reduction to ammonia

Abstract: The production of synthetic ammonia remains dependent on the energy- and capital-intensive Haber–Bosch process. Extensive research in molecular catalysis has demonstrated ammonia production from dinitrogen, albeit at low production rates. Mechanistic understanding of dinitrogen reduction to ammonia continues to be delineated through study of molecular catalyst structure, as well as through understanding the naturally occurring nitrogenase enzyme. The transition to Haber–Bosch alternatives through robust, heterogeneous catalyst surfaces remains an unsolved research challenge. Catalysts for electrochemical reduction of dinitrogen to ammonia are a specific focus of research, due to the potential to compete with the Haber–Bosch process and reduce associated carbon dioxide emissions. However, limited progress has been made to date, as most electrocatalyst surfaces lack specificity towards nitrogen fixation. In this Review, we discuss the progress of the field in developing a mechanistic understanding of nitrogenase-promoted and molecular catalyst-promoted ammonia synthesis and provide a review of the state of the art and scientific needs for heterogeneous electrocatalysts. The artificial synthesis of ammonia remains one of the most important catalytic processes worldwide, over 100 years after its development. In this Review, recent developments in enzymatic, homogeneous and heterogeneous catalysis towards the conversion of nitrogen to ammonia are discussed, with a particular focus on how mechanistic understanding informs catalyst design.

Soil protists: a fertile frontier in soil biology research.

Abstract: Protists include all eukaryotes except plants, fungi and animals. They are an essential, yet often forgotten, component of the soil microbiome. Method developments have now furthered our understanding of the real taxonomic and functional diversity of soil protists. They occupy key roles in microbial foodwebs as consumers of bacteria, fungi and other small eukaryotes. As parasites of plants, animals and even of larger protists, they regulate populations and shape communities. Pathogenic forms play a major role in public health issues as human parasites, or act as agricultural pests. Predatory soil protists release nutrients enhancing plant growth. Soil protists are of key importance for our understanding of eukaryotic evolution and microbial biogeography. Soil protists are also useful in applied research as bioindicators of soil quality, as models in ecotoxicology and as potential biofertilizers and biocontrol agents. In this review, we provide an overview of the enormous morphological, taxonomical and functional diversity of soil protists, and discuss current challenges and opportunities in soil protistology. Research in soil biology would clearly benefit from incorporating more protistology alongside the study of bacteria, fungi and animals.

Justify your alpha

Abstract: In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

Past and future global transformation of terrestrial ecosystems under climate change

Abstract: Impacts of global climate change on terrestrial ecosystems are imperfectly constrained by ecosystem models and direct observations. Pervasive ecosystem transformations occurred in response to warming and associated climatic changes during the last glacial-to-interglacial transition, which was comparable in magnitude to warming projected for the next century under high-emission scenarios. We reviewed 594 published paleoecological records to examine compositional and structural changes in terrestrial vegetation since the last glacial period and to project the magnitudes of ecosystem transformations under alternative future emission scenarios. Our results indicate that terrestrial ecosystems are highly sensitive to temperature change and suggest that, without major reductions in greenhouse gas emissions to the atmosphere, terrestrial ecosystems worldwide are at risk of major transformation, with accompanying disruption of ecosystem services and impacts on biodiversity.

2D Intrinsic Ferromagnets from van der Waals Antiferromagnets.

Abstract: Intrinsically ferromagnetic 2D semiconductors are essential and highly sought for nanoscale spintronics, but they can only be obtained from ferromagnetic bulk crystals, while the possibility to create 2D intrinsic ferromagnets from bulk antiferromagnets remains unknown. Herein on the basis of ab initio calculations, we demonstrate this feasibility with the discovery of intrinsic ferromagnetism in an emerging class of single-layer 2D semiconductors CrOX (CrOCl and CrOBr monolayers), which show robust ferromagnetic ordering, large spin polarization, and high Curie temperature. These 2D crystals promise great dynamical and thermal stabilities as well as easy experimental fabrication from their bulk antiferromagnets. The Curie temperature of 2D CrOCl is 160 K, which exceeds the record (155 K) of the most-studied dilute magnetic GaMnAs materials, and could be further enhanced by appropriate strains. Our study offers an alternative promising way to create 2D intrinsic ferromagnets from their antiferromagnetic b...

The role of the solid electrolyte interphase layer in preventing Li dendrite growth in solid-state batteries

Abstract: Lithium (Li) metal anodes have regained intensive interest in recent years due to the ever-increasing demand for next-generation high energy battery technologies. Li metal, unfortunately, suffers from poor cycling stability and low efficiency as well as from the formation of dangerous Li dendrites, raising safety concerns. Utilizing solid-state electrolytes (SSEs) to prevent Li dendrite growth provides a promising approach to tackle the challenge. However, recent studies indicate that Li dendrites easily form at high current densities, which calls for full investigation of the fundamental mechanisms of Li dendrite formation within SSEs. Herein, the origin and evolution of Li dendrite growth through SSEs have been studied and compared by using Li6.1Ga0.3La3Zr2O12 (LLZO) and NASICON-type Li2O–Al2O3–P2O5–TiO2–GeO2 (LATP) pellets as the separators. We discover that a solid electrolyte interphase (SEI)-like interfacial layer between Li and SSE plays a critical role in alleviating the growth of dendritic Li, providing new insights into the interface between SSE and Li metal to enable future all solid-state batteries.

Guidelines for Adolescent Depression in Primary Care (GLAD-PC): Part I. Practice Preparation, Identification, Assessment, and Initial Management

Abstract: OBJECTIVES: To update clinical practice guidelines to assist primary care (PC) clinicians in the management of adolescent depression. This part of the updated guidelines is used to address practice preparation, identification, assessment, and initial management of adolescent depression in PC settings. METHODS: By using a combination of evidence- and consensus-based methodologies, guidelines were developed by an expert steering committee in 2 phases as informed by (1) current scientific evidence (published and unpublished) and (2) draft revision and iteration among the steering committee, which included experts, clinicians, and youth and families with lived experience. RESULTS: Guidelines were updated for youth aged 10 to 21 years and correspond to initial phases of adolescent depression management in PC, including the identification of at-risk youth, assessment and diagnosis, and initial management. The strength of each recommendation and its evidence base are summarized. The practice preparation, identification, assessment, and initial management section of the guidelines include recommendations for (1) the preparation of the PC practice for improved care of adolescents with depression; (2) annual universal screening of youth 12 and over at health maintenance visits; (3) the identification of depression in youth who are at high risk; (4) systematic assessment procedures by using reliable depression scales, patient and caregiver interviews, and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria; (5) patient and family psychoeducation; (6) the establishment of relevant links in the community, and (7) the establishment of a safety plan. CONCLUSIONS: This part of the guidelines is intended to assist PC clinicians in the identification and initial management of adolescents with depression in an era of great clinical need and shortage of mental health specialists, but they cannot replace clinical judgment; these guidelines are not meant to be the sole source of guidance for depression management in adolescents. Additional research that addresses the identification and initial management of youth with depression in PC is needed, including empirical testing of these guidelines.

Optimal Status Update for Age of Information Minimization With an Energy Harvesting Source

Abstract: In this paper, we consider a scenario where an energy harvesting sensor continuously monitors a system and sends time-stamped status updates to a destination. The destination keeps track of the system status through the received updates. We use the metric Age of Information (AoI), the time that has elapsed since the last received update was generated, to measure the “freshness” of the status information available at the destination. Our objective is to design optimal online status update policies to minimize the long-term average AoI, subject to the energy causality constraint at the sensor. We consider three scenarios, i.e., the battery size is infinite, finite, and one unit only, respectively. For the infinite battery scenario, we adopt a best-effort uniform status update policy and show that it minimizes the long-term average AoI. For the finite battery scenario, we adopt an energy-aware adaptive status update policy, and prove that it is asymptotically optimal when the battery size goes to infinity. For the last scenario where the battery size is one, we first show that within a broadly defined class of online policies, the optimal policy should have a renewal structure. We then focus on a renewal interval, and prove that the optimal policy should have a threshold structure, i.e., if the AoI in the system is below a threshold when an energy arrival enters an empty battery, the sensor should store the energy first and then update when the AoI reaches the threshold; otherwise, it updates the status immediately. Simulation results corroborate the theoretical bounds.

Interplay between Kitaev interaction and single ion anisotropy in ferromagnetic CrI 3 and CrGeTe 3 monolayers

Abstract: Magnetic anisotropy is crucially important for the stabilization of two-dimensional (2D) magnetism, which is rare in nature but highly desirable in spintronics and for advancing fundamental knowledge. Recent works on CrI3 and CrGeTe3 monolayers not only led to observations of the long-time-sought 2D ferromagnetism, but also revealed distinct magnetic anisotropy in the two systems, namely Ising behavior for CrI3 versus Heisenberg behavior for CrGeTe3. Such magnetic difference strongly contrasts with structural and electronic similarities of these two materials, and understanding it at a microscopic scale should be of large benefits. Here, first-principles calculations are performed and analyzed to develop a simple Hamiltonian, to investigate magnetic anisotropy of CrI3 and CrGeTe3 monolayers. The anisotropic exchange coupling in both systems is surprisingly determined to be of Kitaev-type. Moreover, the interplay between this Kitaev interaction and single ion anisotropy (SIA) is found to naturally explain the different magnetic behaviors of CrI3 and CrGeTe3. Finally, both the Kitaev interaction and SIA are further found to be induced by spin–orbit coupling of the heavy ligands (I of CrI3 or Te of CrGeTe3) rather than the commonly believed 3d magnetic Cr ions. Interplay between two anisotropic interactions—Kitaev and single-ion—is responsible for magnetism in ferromagnetic thin films. Teams led by Hongjun Xiang at Fudan University in China and Laurent Bellaiche at the University of Arkansas in the US led to the use of first-principles calculations to elucidate magnetic anisotropy in two different two-dimensional ferromagnetic materials with different magnetic behaviors. By developing a predictive Hamiltonian and a tight-binding model, the origin of two-dimensional magnetism in chromium–iodine and chromium–germanium–tellurium monolayers was revealed to be Kitaev interactions and their interplay with single-ion anisotropy. Both the Kitaev and single-ion anisotropies were induced by the spin–orbit coupling of the heavy ligand elements iodine and tellurium. Research into Kitaev interactions in unconventional systems may contribute towards better understanding of interesting physics.

Environmental and Soil Factors Affecting Micronutrient Deficiencies and Toxicities

Abstract: The availability of the essential micro nutrients B, Cu, Fe, Mn, Mo, and Zn to plants is often poorly related to the total quantity of the particular element in the soil. Soil properties such as pH, redox potential, organic matter content, nutrient interactions, the type of plant or variety, and environmental factors, such as soil water content, temperature and light, greatly influence the likelihood that a plant will exhibit micronutrient-deficiency or -toxicity symptoms. Changes in the environment often have a greater effect on micronutrient than on macro nutrient nutrition of plants. This chapter emphasizes advances in knowledge since Lucas and Knezek's (1972) review in the first edition of this book. In addition, greater emphasis than is customary will be placed on the role of the environment on micronutrient nutrition. Other general references that contain material on this topic are available (Adriano, 1986; Bergmann, 1988; Marschner, 1986; Mengel & Kirkby, 1987; Weber, 1971; and Wild, 1988). Some excellent reference sources include the specific contributions of Keren and Bingham (1985) and Fleming (1980) on B, of Loneragan et al. (1981) on Cu, of Jones (1982, 1984, 1986, and 1988) on Fe, of Graham et al. (1988) on Mn, of Gupta and Lipsett (1981) on Mo, and of Adriano (1986) on Zn. The comprehensive study of Sillanpaa (1982) provides much useful information concerning micronutrient uptake by plants and selected soil properties.

Synthesis of Gold Nanoparticles Using Leaf Extract of Ziziphus zizyphus and their Antimicrobial Activity.

Abstract: (1) Background: There is a growing need for the development of new methods for the synthesis of nanoparticles. The interest in such particles has raised concerns about the environmental safety of their production methods; (2) Objectives: The current methods of nanoparticle production are often expensive and employ chemicals that are potentially harmful to the environment, which calls for the development of “greener” protocols. Herein we describe the synthesis of gold nanoparticles (AuNPs) using plant extracts, which offers an alternative, efficient, inexpensive, and environmentally friendly method to produce well-defined geometries of nanoparticles; (3) Methods: The phytochemicals present in the aqueous leaf extract acted as an effective reducing agent. The generated AuNPs were characterized by Transmission electron microscopy (TEM), Scanning electron microscope (SEM), and Atomic Force microscopy (AFM), X-ray diffraction (XRD), UV-visible spectroscopy, energy dispersive X-ray (EDX), and thermogravimetric analyses (TGA); (4) Results and Conclusions: The prepared nanoparticles were found to be biocompatible and exhibited no antimicrobial or antifungal effect, deeming the particles safe for various applications in nanomedicine. TGA analysis revealed that biomolecules, which were present in the plant extract, capped the nanoparticles and acted as stabilizing agents.

FairGAN: Fairness-aware Generative Adversarial Networks

Abstract: Fairness-aware learning is increasingly important in data mining. Discrimination prevention aims to prevent discrimination in the training data before it is used to conduct predictive analysis. In this paper, we focus on fair data generation that ensures the generated data is discrimination free. Inspired by generative adversarial networks (GAN), we present fairness-aware generative adversarial networks, called FairGAN, which are able to learn a generator producing fair data and also preserving good data utility. Compared with the naive fair data generation models, FairGAN further ensures the classifiers which are trained on generated data can achieve fair classification on real data. Experiments on a real dataset show the effectiveness of FairGAN.

Experimental demonstration of a three-dimensional lithium niobate nonlinear photonic crystal

Abstract: A nonlinear photonic crystal (NPC)1 possesses space-dependent second-order nonlinear coefficients, which can effectively control nonlinear optical interactions through quasi-phase matching2. Lithium niobate (LiNbO3) crystal is one of the most popular materials from which to fabricate NPC structures because of its excellent nonlinear optical properties3–5. One- and two-dimensional LiNbO3 NPCs have been widely utilized in laser frequency conversion6,7, spatial light modulation8–12 and nonlinear optical imaging13,14. However, limited by traditional poling methods, the experimental realization of three-dimensional (3D) NPCs remains one of the greatest challenges in the field of nonlinear optics1,15. Here, we present an experimental demonstration of a 3D LiNbO3 NPC by using a femtosecond laser to selectively erase the nonlinear coefficients in a LiNbO3 crystal16,17. The effective conversion efficiency is comparable to that of typical quasi-phase-matching processes. Such a 3D LiNbO3 NPC provides a promising platform for future nonlinear optical studies based on its unique ability to control nonlinear interacting waves in 3D configuration. By selectively erasing the nonlinear coefficients in a lithium niobate crystal using a femtosecond laser, a 3D nonlinear photonic crystal, with an effective conversion efficiency comparable to that of the typical quasi-phase-matching processes, is demonstrated.

The Psychological Science Accelerator: Advancing Psychology through a Distributed Collaborative Network

Abstract: Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.

Si-Based GeSn Lasers with Wavelength Coverage of 2–3 μm and Operating Temperatures up to 180 K

Abstract: A Si-based monolithic laser is strongly desired for the full integration of Si-photonics. Lasing from the direct bandgap group-IV GeSn alloy has opened a new avenue, different from the hybrid III–V-on-Si integration approach. We demonstrated optically pumped GeSn lasers on Si with broad wavelength coverage from 2 to 3 μm. The GeSn alloys were grown using newly developed approaches with an industry standard chemical vapor deposition reactor and low-cost commercially available precursors. The achieved maximum Sn composition of 17.5% exceeded the generally acknowledged Sn incorporation limits found with similar deposition chemistries. The highest lasing temperature was measured as 180 K with the active layer thickness as thin as 260 nm. The unprecedented lasing performance is mainly due to the unique growth approaches, which offer high-quality epitaxial materials. The results reported in this work show a major advance toward Si-based mid-infrared laser sources for integrated photonics.

Keeping global warming within 1.5 °C constrains emergence of aridification

Abstract: Aridity—the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET)—is projected to decrease (that is, areas will become drier) as a consequence of anthropogenic climate change, exacerbating land degradation and desertification 1–6 . However, the timing of significant aridification relative to natural variability—defined here as the time of emergence for aridification (ToEA)—is unknown, despite its importance in designing and implementing mitigation policies 7–10 . Here we estimate ToEA from projections of 27 global climate models (GCMs) under representative concentration pathways (RCPs) RCP4.5 and RCP8.5, and in doing so, identify where emergence occurs before global mean warming reaches 1.5 °C and 2 °C above the pre-industrial level. On the basis of the ensemble median ToEA for each grid cell, aridification emerges over 32% (RCP4.5) and 24% (RCP8.5) of the total land surface before the ensemble median of global mean temperature change reaches 2 °C in each scenario. Moreover, ToEA is avoided in about two-thirds of the above regions if the maximum global warming level is limited to 1.5 °C. Early action for accomplishing the 1.5 °C temperature goal can therefore markedly reduce the likelihood that large regions will face substantial aridification and related impacts. Arid regions are projected to expand in the future. An ensemble of climate model simulations reveals that limiting anthropogenic warming to 1.5 °C instead of 2 °C can markedly reduce the area undergoing, and thus the population exposed to, aridification.

Comparative studies on copper adsorption by graphene oxide and functionalized graphene oxide nanoparticles

Abstract: In this study, the graphene oxide (GO) was made from graphite powder via a modified Hummers method, then carboxylated to GO COOH in a mixture of a strong basic pH from mixing in the chloroacetic acid with NaOH. The GO and GO COOH were characterized by means of the HR-TEM, FTIR, XRD and zeta potential. On this basis, the Cu(II) was adsorbed onto the GO and GO COOH in aqueous solutions using the simple batch-adsorption mode. The amount of thus-removed Cu(II) was successfully varied, depending on the pH values, initial copper concentration, reaction time and reaction temperature. Under the ambient temperature at pH 6 over 60-min adsorption time, the highest removal efficiency of Cu2+ are 97 and 99.4%, respectively. The experimental data agree well with the Langmuir isotherm in both cases, and the maximum adsorption capacities of GO and GO COOH are 277.77 and 357.14 (mg/g), respectively. The metal adsorption of the GO COOH is better than other carbonaceous adsorbents, and is exothermic and spontaneous from the calculations of chemical thermodynamics. The effect of competing cations on adsorption of Cu(II) ions on GO and GO COOH was evaluated by mono and divalent metals. The reusability of GO and GO COOH were estimated and it was found that both adsorbents have good regeneration properties.

Hidden state models improve state-dependent diversification approaches, including biogeographical models.

Abstract: The state-dependent speciation and extinction (SSE) models have recently been criticized due to their high rates of "false positive" results. Many researchers have advocated avoiding SSE models in favor of other "nonparametric" or "semiparametric" approaches. The hidden Markov modeling (HMM) approach provides a partial solution to the issues of model adequacy detected with SSE models. The inclusion of "hidden states" can account for rate heterogeneity observed in empirical phylogenies and allows for reliable detection of state-dependent diversification or diversification shifts independent of the trait of interest. However, the adoption of HMM has been hampered by the interpretational challenges of what exactly a "hidden state" represents, which we clarify herein. We show that HMMs in combination with a model-averaging approach naturally account for hidden traits when examining the meaningful impact of a suspected "driver" of diversification. We also extend the HMM to the geographic state-dependent speciation and extinction (GeoSSE) model. We test the efficacy of our "GeoHiSSE" extension with both simulations and an empirical dataset. On the whole, we show that hidden states are a general framework that can distinguish heterogeneous effects of diversification attributed to a focal character.

The rice blast resistance gene Ptr encodes an atypical protein required for broad-spectrum disease resistance.

Abstract: Plant resistance genes typically encode proteins with nucleotide binding site-leucine rich repeat (NLR) domains. Here we show that Ptr is an atypical resistance gene encoding a protein with four Armadillo repeats. Ptr is required for broad-spectrum blast resistance mediated by the NLR R gene Pi-ta and by the associated R gene Pi-ta2. Ptr is expressed constitutively and encodes two isoforms that are mainly localized in the cytoplasm. A two base pair deletion within the Ptr coding region in the fast neutron-generated mutant line M2354 creates a truncated protein, resulting in susceptibility to M. oryzae. Targeted mutation of Ptr in a resistant cultivar using CRISPR/Cas9 leads to blast susceptibility, further confirming its resistance function. The cloning of Ptr may aid in the development of broad spectrum blast resistant rice.

High-redshift AGN in the Chandra Deep Fields: the obscured fraction and space density of the sub-L * population

Abstract: We investigate the population of high-redshift (3≤z 23 is ~0.6-0.8, once incompleteness effects are taken into account, with no strong dependence on redshift or luminosity. We derived the high-redshift AGN number counts down to F0.5-2 keV = 7 × 10-18 erg cm-2 s-1, extending previous results to fainter fluxes, especially at z > 4. We put the tightest constraints to date on the low-luminosity end of AGN luminosity function at high redshift. The space density, in particular, declines at z > 3 at all luminosities, with only a marginally steeper slope for low-luminosity AGN. By comparing the evolution of the AGN and galaxy densities, we suggest that such a decline at high luminosities is mainly driven by the underlying galaxy population, while at low luminosities there are hints of an intrinsic evolution of the parameters driving nuclear activity. Also, the black hole accretion rate density and star formation rate density, which are usually found to evolve similarly at z ≲ 3, appear to diverge at higher redshifts. (Less)

detritalPy: A Python-based toolset for visualizing and analysing detrital geo-thermochronologic data

Abstract: Detrital geochronology and thermochronology have emerged as primary methods of reconstructing the tectonic and surficial evolution of the Earth over geological time. Technological improvements in the acquisition of detrital geo‐thermochronologic data have resulted in a rapid increase in the quantity of published data over the past two decades, particularly for the mineral zircon. However, existing tools for visualizing and analysing detrital geo‐thermochronologic data generally lack flexibility for working with large datasets, hampering efforts to utilize the large quantity of available data.

Multiscale analyses and characterizations of surface topographies

Abstract: This work studies multiscale analyses and characterizations of surface topographies from the engineering and scientific literature with an emphasis on production engineering research and design It highlights methods that provide strong correlations between topographies and performance or topographies and processes, and methods that can confidently discriminate topographies that were processed or that perform differently These methods have commonalities in geometric characterizations at certain scales, which are observable with statistics and measurements It also develops a semantic and theoretical framework and proposes a new system for organizing and designating multiscale analyses Finally, future possibilities for multiscale analyses are discussed

Organic Acids and Potential for Modifying the Avian Gastrointestinal Tract and Reducing Pathogens and Disease

Abstract: Recently, antibiotics have been withdrawn from some poultry diets; leaving the birds at risk for increased incidence of dysbacteriosis and disease. Furthermore, mortalities occurring from disease contribute between 10 to 20% of production cost in developed countries. Currently, numerous feed supplements are being proposed as effective antibiotic alternatives in poultry diets, such as prebiotics, probiotics, acidic compounds, competitive exclusion products, herbs, essential oils, and bacteriophages. However, acidic compounds consisting of organic acids show promise as antibiotic alternatives. Organic acids have demonstrated the capability to enhance poultry performance by altering the pH of the gastrointestinal tract (GIT) and consequently changing the composition of the microbiome. In addition, organic acids, by altering the composition of the microbiome, protect poultry from pH-sensitive pathogens. Protection is further provided to poultry by the ability of organic acids to potentially enhance the morphology and physiology of the GIT and the immune system. Thus, the objective of the current review is to provide an understanding of the effects organic acids have on the microbiome of poultry and the effect those changes have on the prevalence of pathogens and diseases in poultry. From data reviewed, it can be concluded that the efficacy of organic acids on shifting microbiome composition is limited to the time of administration, the composition of the organic acid product, and the current health conditions of poultry.

Cavity-Free Optical Isolators and Circulators Using a Chiral Cross-Kerr Nonlinearity

Abstract: Optical nonlinearity has been widely used to try to produce optical isolators. However, this is very difficult to achieve due to dynamical reciprocity. Here, we show the use of the chiral cross-Kerr nonlinearity of atoms at room temperature to realize optical isolation, circumventing dynamical reciprocity. In our approach, the chiral cross-Kerr nonlinearity is induced by the thermal motion of $N$-type atoms. The resulting cross phase shift and absorption of a weak probe field are dependent on its propagation direction. This proposed optical isolator can achieve more than 30 dB of isolation ratio, with a low loss of less than 1 dB. By inserting this atomic medium in a Mach-Zehnder interferometer, we further propose a four-port optical circulator with a fidelity larger than 0.9 and an average insertion loss less than 1.6 dB. Using atomic vapor embedded in an on-chip waveguide, our method may provide chip-compatible optical isolation at the single-photon level of a probe field.

Mapping metabolic changes by noninvasive, multiparametric, high-resolution imaging using endogenous contrast.

Abstract: Monitoring subcellular functional and structural changes associated with metabolism is essential for understanding healthy tissue development and the progression of numerous diseases, including cancer, diabetes, and cardiovascular and neurodegenerative disorders. Unfortunately, established methods for this purpose either are destructive or require the use of exogenous agents. Recent work has highlighted the potential of endogenous two-photon excited fluorescence (TPEF) as a method to monitor subtle metabolic changes; however, mechanistic understanding of the connections between the detected optical signal and the underlying metabolic pathways has been lacking. We present a quantitative approach to detecting both functional and structural metabolic biomarkers noninvasively, relying on endogenous TPEF from two coenzymes, NADH (reduced form of nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide). We perform multiparametric analysis of three optical biomarkers within intact, living cells and three-dimensional tissues: cellular redox state, NADH fluorescence lifetime, and mitochondrial clustering. We monitor the biomarkers in cells and tissues subjected to metabolic perturbations that trigger changes in distinct metabolic processes, including glycolysis and glutaminolysis, extrinsic and intrinsic mitochondrial uncoupling, and fatty acid oxidation and synthesis. We demonstrate that these optical biomarkers provide complementary insights into the underlying biological mechanisms. Thus, when used in combination, these biomarkers can serve as a valuable tool for sensitive, label-free identification of changes in specific metabolic pathways and characterization of the heterogeneity of the elicited responses with single-cell resolution.