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Conjugated polymers (CPs) represent a promising platform for photocatalytic CO2 fixation owing to their suitable band structures that meet the requirements of the reduction potential of CO2 to value‐added fuels. However, the photocatalytic performance of CPs is rather restrained by the low charge transfer efficiency. Herein, we rationally designed three CPs with a more delocalized electronic transmission channel and planar molecular structure, which are regarded to evidently reduce the exciton binding energy (Eb) and accelerate the internal charge transfer process. Besides, the assembly of suitable electron‐output "tentacles" and cocatalysts on the surface of CPs could effectively facilitate interfacial electron delivery. Accordingly, the optimal P‐2CN exhibits an apparent quantum yield of 4.6 % at 420 nm for photocatalytic CO2 to CO. Further adjusting the amounts of cyano groups and cocatalysts, the CO selectivity could be obtained in the range of 0–80.5 %. [ABSTRACT FROM AUTHOR]

Conjugated polymers (CPs) represent a promising platform for photocatalytic CO2 fixation owing to their suitable band structures that meet the requirements of the reduction potential of CO2 to value‐added fuels. However, the photocatalytic performance of CPs is rather restrained by the low charge transfer efficiency. Herein, we rationally designed three CPs with a more delocalized electronic transmission channel and planar molecular structure, which are regarded to evidently reduce the exciton binding energy (Eb) and accelerate the internal charge transfer process. Besides, the assembly of suitable electron‐output "tentacles" and cocatalysts on the surface of CPs could effectively facilitate interfacial electron delivery. Accordingly, the optimal P‐2CN exhibits an apparent quantum yield of 4.6 % at 420 nm for photocatalytic CO2 to CO. Further adjusting the amounts of cyano groups and cocatalysts, the CO selectivity could be obtained in the range of 0–80.5 %. [ABSTRACT FROM AUTHOR]

Conjugated polymers (CPs) have garnered increasing attention in the field of photocatalysis due to their stability and molecular tunability. Understanding the structure–property relationship in CPs and addressing appropriate molecular design strategies are pivotal to improving the photocatalytic performance of CPs. Herein, a new efficient cyano (CN) engineering approach was proposed to promote the photocatalytic performance of CPs, and three representative CP‐based photocatalysts with different CN contents were tailor‐made to investigate the relationship between CN functionalization and photocatalytic activity. A series of systematically experimental and theoretical studies reveal that CN functionalization contributes to strengthening the donor‐acceptor (D‐A) interaction, enhancing the light absorption ability, charge separation/transfer efficiency, and hydrophilicity of CPs, and also facilitating the output of separated photoinduced electrons from CPs to Pt cocatalyst. Thus, the dicyano‐functionalized polymer (P‐2CN) manifests an attractive photocatalytic performance in hydrogen production. This study provides a facile strategy to develop excellent CP‐based photocatalysts for solar fuel production. [ABSTRACT FROM AUTHOR]

Prudent risk management requires consideration of bad-to-worst-case scenarios. Yet, for climate change, such potential futures are poorly understood. Could anthropogenic climate change result in worldwide societal collapse or even eventual human extinction? At present, this is a dangerously underexplored topic. Yet there are ample reasons to suspect that climate change could result in a global catastrophe. Analyzing the mechanisms for these extreme consequences could help galvanize action, improve resilience, and inform policy, including emergency responses. We outline current knowledge about the likelihood of extreme climate change, discuss why understanding bad-to-worst cases is vital, articulate reasons for concern about catastrophic outcomes, define key terms, and put forward a research agenda. The proposed agenda covers four main questions: 1) What is the potential for climate change to drive mass extinction events? 2) What are the mechanisms that could result in human mass mortality and morbidity? 3) What are human societies' vulnerabilities to climate-triggered risk cascades, such as from conflict, political instability, and systemic financial risk? 4) How can these multiple strands of evidence--together with other global dangers--be usefully synthesized into an "integrated catastrophe assessment"? It is time for the scientific community to grapple with the challenge of better understanding catastrophic climate change. [ABSTRACT FROM AUTHOR]

In this article, a temperature-dependent threshold voltage extraction method based on noise measurement is proposed. This method induces a mathematical solution for acquiring channel temperatures ($T$) of transistors in the saturation region to extract threshold voltages. In order to gain accurate channel temperature, a small-signal equivalent circuit model was established to determine transconductance ($g_{m}$). Then, the extracted transconductance and measured noise power spectral density (NPSD) were used to obtain channel temperatures. On this basis, the temperature-dependent threshold voltage ($V_{\mathrm {th}}$) was derived. To validate the reliability of this method, a four-Fin six-finger N-FinFET and a four-Fin eight-finger N-FinFET were fabricated using the 14-nm bulk FinFET technology. In this study, the scattering parameters were obtained from 0.2 to 40.2 GHz. Also, the NPSDs were measured from 1 to 500 Hz, while gate voltage and drain voltage were set as 0.3, 0.49, and 0.75 V. Besides, the transistor $I_{\mathrm {ds}}$ – $V_{\mathrm {ds}}$ characteristics was also investigated when drain–source bias voltage changed from 0.05 to 0.9 V. Compared with the measurement results, the calculation results of drain–source current model using temperature-dependent threshold voltage achieved higher accuracy. Also, the root mean square errors (RMSEs) were less than 0.60% for four-Fin six-finger N-FinFET and less than 0.51% for four-Fin eight-finger N-FinFET. Therefore, the proposed extraction method can be applied to accurately predict transistor temperature-dependent threshold voltage. [ABSTRACT FROM AUTHOR]

The compositional dependence of the lattice parameter in Ge1-ySny alloys has been determined from combined X-ray diffraction and Rutherford Backscattering (RBS) measurements of a large set of epitaxial films with compositions in the 0

Economic inequality is notoriously difficult to quantify as reliable data on household incomes are missing for most of the world. Here, we show that a proxy for inequality based on remotely sensed nighttime light data may help fill this gap. Individual households cannot be remotely sensed. However, as households tend to segregate into richer and poorer neighborhoods, the correlation between light emission and economic thriving shown in earlier studies suggests that spatial variance of remotely sensed light per person might carry a signal of economic inequality. To test this hypothesis, we quantified Gini coefficients of the spatial variation in average nighttime light emitted per person. We found a significant relationship between the resulting light-based inequality indicator and existing estimates of net income inequality. This correlation between light-based Gini coefficients and traditional estimates exists not only across countries, but also on a smaller spatial scale comparing the 50 states within the United States. The remotely sensed character makes it possible to produce high-resolution global maps of estimated inequality. The inequality proxy is entirely independent from traditional estimates as it is based on observed light emission rather than self-reported household incomes. Both are imperfect estimates of true inequality. However, their independent nature implies that the light-based proxy could be used to constrain uncertainty in traditional estimates. More importantly, the light-based Gini maps may provide an estimate of inequality where previously no data were available at all. [ABSTRACT FROM AUTHOR]

BACKGROUND Most of the widely used methods for the assessment of keloid treatment are subjective grading scales based on the opinion of an individual clinician or patient. There is a growing need for objective methods to evaluate keloid treatment. OBJECTIVE This study aimed to evaluate the value of laser speckle contrast imaging (LSCI) as an objective method for the assessment of dual-wavelength laser therapy for keloids. METHODS This prospective study included 21 patients with 54 keloids. All patients were treated with a combined 585-nm pulsed dye laser and 1,064 nm neodymium-doped yttrium aluminum garnet dual-wavelength laser at 4 weeks to 6 weeks intervals. Keloids were assessed using the Vancouver Scar Scale (VSS) and LSCI. RESULTS The total VSS score significantly decreased after 4 sessions of treatment (p < .05). Blood perfusion in keloids as measured by LSCI was significantly reduced after treatment (p < .05). The improvement of chest keloids in terms of the total VSS score and blood perfusion was significantly greater than that of scapular keloids (p < .05). There was a positive correlation between decreased perfusion and reduced total VSS score (R² = 0.84). CONCLUSION Blood perfusion in keloids significantly decreased after dual-wavelength laser therapy. Laser speckle contrast imaging is a promising objective method for assessing the improvement of keloids treated with laser therapy. [ABSTRACT FROM AUTHOR]

Background: Pathway analysis is widely applied in transcriptome analysis. Given certain transcriptomic changes, current pathway analysis tools tend to search for the most impacted pathways, which provides insight into underlying biological mechanisms. Further refining of the enriched pathways and extracting functional modules by “crosstalk” analysis have been proposed. However, the upstream/downstream relationships between the modules, which may provide extra biological insights such as the coordination of different functional modules and the signal transduction flow have been ignored. Results: To quantitatively analyse the upstream/downstream relationships between functional modules, we developed a novel GEne Set Topological Impact Analysis (GESTIA), which could be used to assemble the enriched pathways and functional modules into a super-module with a topological structure. We showed the advantages of this analysis in the exploration of extra biological insight in addition to the individual enriched pathways and functional modules. Conclusions: GESTIA can be applied to a broad range of pathway/module analysis result. We hope that GESTIA may help researchers to get one additional step closer to understanding the molecular mechanism from the pathway/module analysis results. [ABSTRACT FROM AUTHOR]

Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig. [ABSTRACT FROM AUTHOR]

Introduction: We aimed to explore the risk factors for periprosthetic joint infection (PJI) after primary artificial hip and knee joint replacements by performing a case-control study. Methodology: The clinical data of patients receiving primary hip and knee joint replacements were retrospectively analyzed. The case group included 96 patients who suffered from PJI, comprising 42 cases of hip joint replacement and 54 cases of knee joint replacement. Another 192 patients who received joint replacement at the ratio of 1:2 in the same period and did not suffer from PJI were selected as the control group. Differences between the two groups were compared in regard to etiology, pathogen, blood type, urine culture, body mass index (BMI), surgical time, intraoperative blood loss, postoperative 1st day and total drainage volumes, length of hospitalization stay, and history of surgery at the affected sites. Results: Gram-positive bacteria were the main pathogens for PJI. The most common infection after hip joint replacement was caused by Staphylococcus epidermidis, which accounted for 38.10%, while Staphylococcus aureus was mainly responsible for the infection of knee joint (40.74%). High BMI, long surgical time, large postoperative drainage volume, long hospitalization stay, history of surgery at incisions, previous use of immunosuppressants, preoperative hypoproteinemia and superficial infection were independent risk factors (p < 0.05). Conclusions: PJI after primary replacement was mainly caused by gram-positive bacteria, and patients with high BMI, long surgical time, large postoperative drainage volume, long hospitalization stay, history of surgery at incisions, previous use of immunosuppressants, preoperative hypoproteinemia and superficial infection were more vulnerable. [ABSTRACT FROM AUTHOR]

Human activities currently play a dominant role in shaping and eroding Earth's biodiversity, but the historical dynamics leading to this situation are poorly understood and contentious. Importantly, these dynamics are often studied and discussed without an emphasis on cultural evolution, despite its potential importance for past and present biodiversity dynamics. Here, we investigate whether cultural filtering, defined as the impact of cultural evolution on species presence, has driven the range dynamics of five historically widespread megafauna taxa (Asiatic elephant, rhinoceroses, tiger, Asiatic black bear, and brown bear) across China over the past 2 millennia. Data on megafauna and sociocultural history were compiled from Chinese administrative records. While faunal dynamics in China are often linked to climate change at these time scales, our results reveal cultural filtering as the dominant driver of range contractions in all five taxa. This finding suggests that the millennia-long spread of agricultural land and agricultural intensification, often accompanied by expansion of the Han culture, has been responsible for the extirpation of these megafauna species from much of China. Our results suggest that cultural filtering is important for understanding society's role in the assembly of contemporary communities from historical regional species pools. Our study provides direct evidence that cultural evolution since ancient times has overshadowed climate change in shaping broadscale megafauna biodiversity patterns, reflecting the strong and increasing importance of sociocultural processes in the biosphere. [ABSTRACT FROM AUTHOR]

In this paper, a graphical tuning method for controllers parameters based on the open-loop fractional transfer function (FO-EOTF) method is proposed for fractional-order parameter uncertain multivariable system. The FO-EOTF method is proposed to transform the parameter uncertain fractional-order multivariable system into a set of independent parameter uncertain fractional-order univariate systems and determine the parameters regions of the univariate systems. The gain phase margin tester is used to further guarantee the robust performance of the controlled system. Finally, simulation result from the numerical simulation is presented to demonstrate the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Background: Recently, the roles of purinergic receptor P2X ligand-gated ion channel 7 (P2X7) polymorphisms in tuberculosis (TB) were analyzed by some pilot studies, but the results of these studies were inconsistent. We performed this study to better assess the relationship between P2X7 polymorphisms and the odds of TB. Methods: Eligible studies were searched in PubMed, MEDLINE, and Embase. Odds ratios and 95% confidence intervals were calculated. Results: A total of 21 studies were included for analyses. Significant associations with the odds of TB were detected for rs3751143 polymorphism in dominant (p = 0.01), recessive (p < 0.0001), additive (p = 0.0002), and allele models (p < 0.0001) in overall analyses. Further subgroup analyses based on the ethnicity of participants revealed that the rs1718119 polymorphism is significantly associated with the odds of TB in Asians and the rs3751143 polymorphism with the odds of TB in Caucasians. Conclusion: Our findings indicate that rs1718119 polymorphism may serve as a potential biological marker of TB in Asians and the rs3751143 polymorphism as a potential biological marker of TB in Caucasians. [ABSTRACT FROM AUTHOR]

This paper proposes a novel design of a high order closed-loop Sigma-Delta modulator using a fractional-order disturbance observer, which can reduce the influence of possible dispersions of the sensing element and offset the effect of the external disturbance. The proof mass can maintain near its position of equilibrium by using the proposed fractional-order disturbance observer, which ensures a better control of the proof mass displacement, and the small proof mass displacement can enhance the sensor resolution and the overall system performance. Fractional-order disturbance observer possesses stronger robust stability of interference elimination, because the introduction of fractional calculus makes Q-filter expanding from an integer domain to a real-number domain. Experimental results from the proposed architecture shows an increase of more than 2X improved in signal quantization noise ratio compared to the pure high-order closed-loop Sigma-Delta modulator, and also the proposed Sigma-Delta modulator with a fractional-order disturbance observer improves the performance of disturbance attenuation and system robustness. [ABSTRACT FROM AUTHOR]

A schedule-based system is a system that operates on or contains within a schedule of events and breaks at particular time intervals. Entities within the system show presence or absence in these events by entering or exiting the locations of the events. Given radio frequency identification (RFID) data from a schedule-based system, what can we learn about the system (the events and entities) through data mining? Which data mining methods can be applied so that one can obtain rich actionable insights regarding the system and the domain? The research goal of this paper is to answer these posed research questions, through the development of a framework that systematically produces actionable insights for a given schedule-based system. We show that through integrating appropriate data mining methodologies as a unified framework, one can obtain many insights from even a very simple RFID dataset, which contains only very few fields. The developed framework is general, and is applicable to any schedule-based system, as long as it operates under certain basic assumptions. The types of insights are also general, and are formulated in this paper in the most abstract way. The applicability of the developed framework is illustrated through a case study, where real world data from a schedule-based system is analyzed using the introduced framework. Insights obtained include the profiling of entities and events, the interactions between entity and events, and the relations between events. [ABSTRACT FROM AUTHOR]

The performance of the conventional Sigma-Delta modulator can be improved by cascading electrical integrator behind the mechanical sensing element. In this paper, a novel Sigma-Delta modulator with a fractional-order PIλDµ controller is proposed and thus extending the traditional Sigma-Delta modulator to a new fractional-order in the Sigma-Delta ADC design field. The fractional-order PIλDµ controller allows fine tuning accuracy in seeking the coefficients for the proposed Sigma-Delta modulator and provides the robust stability in the placement of poles and zeros for compensating the phase delays. The parameters of the proposed fractional-order Sigma-Delta modulator is designed by using swarm intelligent algorithm, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance. Simulation from the proposed fractional-order Sigma-Delta modulator, results of SNR > 134 dB and the noise floor under -170 dB are obtained in frequency range of [5-150 Hz]. [ABSTRACT FROM AUTHOR]

The performance of the conventional Sigma-Delta modulator can be improved by cascading electrical integrator behind the mechanical sensing element. In this paper, a novel Sigma-Delta modulator with a fractional-order PIλDμ controller is proposed and thus extending the traditional Sigma-Delta modulator to a new fractional-order in the Sigma-Delta ADC design field. The fractional-order PIλDμ controller allows fine tuning accuracy in seeking the coefficients for the proposed Sigma-Delta modulator and provides the robust stability in the placement of poles and zeros for compensating the phase delays. The parameters of the proposed fractional-order Sigma-Delta modulator is designed by using swarm intelligent algorithm, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance. Simulation from the proposed fractional-order Sigma-Delta modulator, results of SNR > 134 dB and the noise floor under -170 dB are obtained in frequency range of [5-150 Hz]. [ABSTRACT FROM AUTHOR]

It is often a challenge to simulate soil moisture dynamics accurately when limited data are available about the soil. A forward simulation based on pedotransfer function (PTF) estimates of hydraulic parameters indeed produced severely biased moisture fluxes. This study therefore evaluated a new model inversion strategy which is able to use limited data by optimizing factors that scale PTF estimates. An important feature of this strategy is that the model inversion is performed for all profiles simultaneously, thus ensuring that the hydraulic parameters among the different profiles are adjusted at the same time by changing the scale factors while also ensuring that sufficient data are available to make inversion mathematically possible. We evaluated three main inversion models of different complexity. The simplest model (GW5), in which there were five scale factors with no horizon distinction was the most parsimonious in terms of the corrected Akaike's Information Criterion (AICc). GW10 (with two sets of five scale factors for topsoil and subsoil) and GW30 (six sets) performed less well in terms of AICc, but were able to simulate the mean observed moisture profile much better than GW5. Additional inversions demonstrated that textural variation was important to achieve the best performance, thus indicating that the PTF estimates are a necessary part of the inversion. The GW5 model parameters appeared to be insensitive to assumptions made about total root water uptake and its distribution within the profile. The inversion method is simple and can be interfaced without much difficulty with existing vadose zone models. [ABSTRACT FROM AUTHOR]

Hybrid (III-V)-(IV) alloys described using the general formula (GaP)y(Si)5-2y have been synthesized as epitaxial layers on Si(100) using specially designed chemical vapor deposition methods. Reactions of [D2GaN(CH3)2]2 with P(SiH3)3 between 525 and 540 °C gave GaPSi3 (y = 1) with a fixed Si content of 60%, while analogous reactions of [H2GaN(CH3)2]2 at >590 °C produced Si-rich derivatives with tunable Si contents in the range of 75-95% (y < 1). In both cases, diffraction studies and optical characterizations demonstrate single-phase, monocrystalline structures with an average diamond cubic lattice akin to Si. Raman scattering supports the presence of a tetrahedral structure containing isolated Ga-P pairs randomly embedded within the parent Si matrix. This outcome is consistent with theoretical simulations of a crystal growth mechanism involving interlinking GaPSi3 tetrahedra in a manner that precludes the formation of energetically unfavorable Ga-Ga bonds. Ellipsometry measurements of the dielectric function reveal systematic tuning of the absorption coefficient as a function of composition and demonstrate an enhanced optical response in the visible range relative to crystalline Si. The seamless integration with Si wafers and the intriguing optical response suggest these materials are promising candidates for optoelectronic applications. [ABSTRACT FROM AUTHOR]

Near-surface soil moisture is a spatially highly heterogeneous state variable that affects the hydrologic partitioning of precipitation, net ecosystem exchange and land-atmosphere interactions. In concert with the rapid advancement of large-scale hyperspectral remote sensing technology over the last decade, numerous methods relating reflectance to near-surface soil moisture have been proposed. Although there is evidence that surface reflectance is conjointly controlled by moisture and salt content, little is known about the impact of soil salinity. To study the effects of soil salinity, near infrared to short-wave infrared reflectance spectra were measured in a controlled laboratory environment for samples representing a wide range of salinity levels. A previously proposed surface moisture prediction method based on geometrical attributes of an inverted Gaussian (IG) function fitted to hyperspectral reflectance curves was revisited. Improvements were proposed by first modifying the geometrical attributes of the IG applied to predict near-surface soil moisture and by concurrently considering multiple geometrical attributes of the IG function as input for trained artificial neural networks (ANNs). Although previously applied linear regression models that relate a single geometrical parameter to soil moisture failed to satisfactorily predict independently measured surface soil moisture, considerable improvements in prediction accuracy were achieved with both geometrical attribute modification and ANN simulations. [ABSTRACT FROM AUTHOR]

Although canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite-borne Li DAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest-savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna-like sparse tree cover that have a forest-like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale. [ABSTRACT FROM AUTHOR]

The lattice parameter of Ge films doped with phosphorus, arsenic, and antimony was measured as a function of the dopant concentration. When the observed trends are compared with similar measurements in doped Si, a clear pattern emerges in support of the Cargill-Keyes theory that computes the doping dependence of the lattice parameter as the sum of a purely electronic contribution, proportional to the absolute deformation potential for the states occupied by the dopant carriers, plus a size mismatch contribution that depends on the universal topological rigidity parameter for Si-Ge systems. It is shown that when considered from the same global perspective, ab initio calculations of the structural effects of doping are in remarkable agreement with the Cargill-Keyes theory. [ABSTRACT FROM AUTHOR]

This research examines the simultaneous retrieval of surface soil moisture and salt concentrations using hyperspectral reflectance data in an arid environment. We conducted laboratory and outdoor field experiments in which we examined three key soil variables: soil moisture, salt and texture (silty loam, clay and silty clay). The soil moisture content models for multiple textures (M_SMC models) were based on selected hyperspectral reflectance data located around 1460, 1900 and 2010 nm and resulted in R² values higher than 0.933. Meanwhile, the soil salt concentrations were also accurately (R² > 0.748) modeled (M_SSC models) based on wavebands located at 540, 1740, 2010 and 2350 nm. When the different texture samples were mixed (SL + C + SC models), soil moisture was still accurately retrieved (R² = 0.937) but the soil salt not as well (R² = 0.47). After stratifying the samples by retrieved soil moisture levels, the R² of calibrated M_SSCSMC models for soil salt concentrations improved to 0.951. This two-step method also showed applicability for analyzing soil-salt samples in the field. The M_SSCSMC models resulted in R² values equal to 0.912 when moisture is lower than 0.15, and R² values equal to 0.481 when soil moisture is between 0.15 and 0.2. [ABSTRACT FROM AUTHOR]

Giant pandas (Ailuropoda melanoleuca) are now confined to fragmented habitats in western China, with more than 60 % of individuals inhabiting 63 protected areas. Knowledge of the environmental features required by giant pandas is critically important for protected area spatial arrangement and subsequent assessments. Here we developed a distribution model for giant pandas in the Tangjiahe Nature Reserve using Ecological Niche Factor Analysis (ENFA) model. We found that less than 40 % of this key reserve is of high suitability for giant pandas, highly suitable habitat being primarily characterized as coniferous forests away from roads within the reserve. Although there was a clear core zone occupied by giant pandas, which included the vast majority of known giant panda locations, only about 45 % of this zone was classified as highly suitable habitat (suitable and optimal). Therefore, the spatial arrangement within the reserve may need to be modified to effectively manage the remaining population of giant pandas. Of particular concern are several tourism proposals being considered by local government, which, if implemented, will increase the isolation of the local population from those in the surrounding area. Our analysis identifies Caijiaba and Baixiongping as areas that should become conservation priorities. Our approach provides valuable data to advise conservation policy and could be easily replicated across other protected areas. [ABSTRACT FROM AUTHOR]

Selective catalytic reduction technology using NH3 as a reducing agent (NH3-SCR) is an effective control method to remove nitrogen oxides. TiO2-supported vanadium oxide catalysts with different levels of Ce and Sb modification were prepared by an impregnation method and were characterized by X-ray diffractometer (XRD), Brunauer-Emmett-Teller (BET), Transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), UV-Vis diffuse reflectance spectroscopy (UV-Vis DRS), Raman and Hydrogen temperature-programmed reduction (H2-TPR). The catalytic activities of V5CexSby/TiO2 catalysts for denitration were investigated in a fixed bed flow microreactor. The results showed that cerium, vanadium and antimony oxide as the active components were well dispersed on TiO2, and the catalysts exhibited a large number of d-d electronic transitions, which were helpful to strengthen SCR reactivity. The V5CexSby/TiO2 catalysts exhibited a good low temperature NH3-SCR catalytic activity. In the temperature range of 210 to 400°C, the V5CexSby/TiO2 catalysts gave NO conversion rates above 90%. For the best V5Ce35Sb2/TiO2 catalyst, at a reaction temperature of 210°C, the NO conversion rate had already reached 90%. The catalysts had different catalytic activity with different Ce loadings. With the increase of Ce loading, the NO conversion rate also increased. [ABSTRACT FROM AUTHOR]

The relationship between carrier concentration and donor atomic concentration has been determined in n-type Ge films doped with P. The samples were carefully engineered to minimize non-active dopant incorporation by using specially designed P(SiH3)3 and P(GeH3)3 hydride precursors. The in situ nature of the doping and the growth at low temperatures, facilitated by the Ge3H8 and Ge4H10 Ge sources, promote the creation of ultra-low resistivity films with flat doping profiles that help reduce the errors in the concentration measurements. The results show that Ge deviates strongly from the incomplete ionization expected when the donor atomic concentration exceeds Nd = 1017cm-3, at which the energy separation between the donor and Fermi levels ceases to be much larger than the thermal energy. Instead, essentially full ionization is seen even at the highest doping levels beyond the solubility limit of P in Ge. The results can be explained using a model developed for silicon by Altermatt and coworkers, provided the relevant model parameter is properly scaled. The findings confirm that donor solubility and/or defect formation, not incomplete ionization, are the major factors limiting the achievement of very high carrier concentrations in n-type Ge. The commercially viable chemistry approach applied here enables fabrication of supersaturated and fully ionized prototypes with potential for broad applications in group-IV semiconductor technologies. [ABSTRACT FROM AUTHOR]

Chemical mutagenesis is routinely used to create large numbers of rare mutations in plant and animal populations, which can be subsequently subjected to selection for beneficial traits and phenotypes that enable the characterization of gene functions. Several next-generation sequencing ( NGS)-based target enrichment methods have been developed for the detection of mutations in target DNA regions. However, most of these methods aim to sequence a large number of target regions from a small number of individuals. Here, we demonstrate an effective and affordable strategy for the discovery of rare mutations in a large sodium azide-induced mutant rice population (F2). The integration of multiplex, semi-nested PCR combined with NGS library construction allowed for the amplification of multiple target DNA fragments for sequencing. The 8 × 8 × 8 tridimensional DNA sample pooling strategy enabled us to obtain DNA sequences of 512 individuals while only sequencing 24 samples. A stepwise filtering procedure was then elaborated to eliminate most of the false positives expected to arise through sequencing error, and the application of a simple Student's t-test against position-prone error allowed for the discovery of 16 mutations from 36 enriched targeted DNA fragments of 1024 mutagenized rice plants, all without any false calls. [ABSTRACT FROM AUTHOR]

This Article describes the development of an optimized chemistry-based synthesis method, supported by a purpose-built reactor technology, to produce the next generation of Ge1-x-ySixSny materials on conventional Si(100) and Ge(100) platforms at gas-source molecular epitaxy conditions. Technologically relevant alloy compositions (1-5% Sn, 4-20% Si) are grown at ultralow temperatures (330-290 °C) using highly reactive tetragermane (Ge4H10), tetrasilane (Si4H10), and stannane (SnD4) hydride precursors, allowing the simultaneous increase of Si and Sn content (at a fixed Si/Sn ratio near 4) for the purpose of tuning the bandgap while maintaining lattice-matching to Ge. First principles thermochemistry studies were used to explain stability and reactivity differences between the Si/Ge hydride sources in terms of a complex interplay among the isomeric species, and provide guidance for optimizing process conditions. Collectively, this approach leads to unprecedented control over the substitutional incorporation of Sn into Si-Ge and yields materials with superior quality suitable for transitioning to the device arena. We demonstrate that both intrinsic and doped Ge1-x-ySixSny layers can now be routinely produced with defect-free microstructure and viable thickness, allowing the fabrication of high-performance photodetectors on Ge(100). Highlights of these new devices include precisely adjustable absorption edges between 0.87 and 1.03 eV, low ideality factors close to unity, and state-of-the-art dark current densities for Ge-based materials. Our unequivocal realization of the "molecules to device" concept implies that GeSiSn alloys represent technologically viable semiconductors that now merit inclusion in the class of ubiquitous Si, Ge, and SiGe group IV systems. [ABSTRACT FROM AUTHOR]

Time of arrival (TOA) estimation in multipath dense environment for UWB backscattering radio frequency identification (RFID) system is challenging due to the presence of strong clutter. In addition, the backscattering RFID system has peculiar signal transmission and modulation characteristics, which are considerably different from conventional communication and localization systems. The existing TOA estimators proposed for conventionalUWBsystems are inappropriate for the backscattering RFID system since they lack the required clutter suppression capability and do not account for the peculiar characteristics of backscattering system. In this paper, we derive a nondata-aided (NDA) least square (LS) TOA estimator for UWB backscattering RFID system. We show that the proposed estimator is inherently immune to clutter and is robust in under-sampling operation. The effects of various parameter settings on the TOA estimation accuracy are also studied via simulations. [ABSTRACT FROM AUTHOR]

The opioid receptors are a member of G protein-coupled receptors that mediate physiological effects of endogenous opioid peptides and structurally distinct opioid alkaloids. Although it is well characterized that there is differential receptor desensitization and internalization properties following activation by distinct agonists, the underlying mechanisms remain elusive. We investigated the signaling events of δ-opioid receptor (δOR) initiated by two ligands, DPDPE and TIPP. We found that although both ligands inhibited adenylyl cyclase (AC) and activated ERK1/2, only DPDPE induced desensitization and internalization of the δOR. We further found that DPDPE, instead of TIPP, could activate GRK2 by phosphorylating the non-receptor tyrosine kinase Src and translocating it to membrane receptors. Activation of GRK2 led to the phosphorylation of serine residues in the C-terminal tail, which facilitates β-arrestin1/2 membrane translocation. Meanwhile, we also found that DPDPE promoted β-arrestin1 dephosphorylation in a Src-dependent manner. Thus, DPDPE appears to strengthen β-arrestin function by dual regulations: promoting β-arrestin recruitment and increasing β-arrestin dephosphorylation at the plasma membrane in a Src-dependent manner. All effects initiated by DPDPE could be abolished or suppressed by PP2, an inhibitor of Src. Morphine, which has been previously shown to be unable to desensitize or internalize δOR, also behaved as TIPP in failure to utilize Src to regulate δOR signaling. These findings point to the existence of agonist-specific utilization of Src to regulate δOR signaling and reveal the molecular events by which Src modulates δOR responsiveness. [ABSTRACT FROM AUTHOR]

At specified Reynolds numbers Re = ρ v c / μ = 5 × 10 5 , this study investigates the power-extraction regime of a flapping-foil turbine executing a figure-eight trajectory. This study thoroughly explored the impacts of trajectory shape, heave and pitch amplitudes, phase difference, and pitch axis location on the power-extraction regime of a flapping turbine. A figure-eight trajectory substantially bolsters the energy harvesting capacity, achieving a peak efficiency of up to 50%. This trajectory capitalizes on the energy generated from the drag encountered by the flapping foil, thereby marking a significant efficiency breakthrough. This could denote a considerable progression for flapping foils tailored for heave and pitch motions since the free stream can be optimally harnessed by the trajectory we have established. In scenarios where the flapping foil undergoes the same maximum effective angle of attack, a wake diffusion spectrum aligns with the Betz limit threshold. Crucially, the closeness to this efficiency frontier suggests a universal maximum effective angle of attack—a consistent law that remains valid for the conventional flapping turbine design. It implies that selections for stroke and pitch amplitudes should be methodical rather than arbitrary. In addition, the positioning of the pitch axis ought to be modified in tandem with phase difference adjustments to bolster the synchronization between heaving motions and resultant lift. The ideal phase difference is variable, contingent on pitch amplitude and pitch axis position. Even with low pitch amplitudes, fine-tuning the phase difference guarantees that the energy harvesting efficiency does not fall below 30%. Such an enhancement would significantly broaden the operational envelope and the parameter space for flapping turbines. [ABSTRACT FROM AUTHOR]

A systematic study of hole compensation effect on magnetic properties, which is controlled by defect compensation through ion irradiation, in (Ga,Mn)As, (In,Mn)As and (Ga,Mn)P is represented in this work. In all materials, both Curie temperature and magnetization decrease upon increasing the hole compensation, confirming the description of hole mediated ferromagnetism according to the p -d Zener model. The material dependence of Curie temperature and magnetization versus hole compensation reveals that the manipulation of magnetic properties in III-Mn-V dilute ferromagnetic semiconductors by ion irradiation is strongly influenced by the energy level location of the produced defect relative to the band edges in semiconductors. [ABSTRACT FROM AUTHOR]

Knowledge bases have been instrumental in advancing biological research, facilitating pathway analysis and data visualization, which are now widely employed in the scientific community. Despite the establishment of several prominent knowledge bases focusing on signaling, metabolic networks, or both, integrating these networks into a unified topological network has proven to be challenging. The intricacy of molecular interactions and the diverse formats employed to store and display them contribute to the complexity of this task. In a prior study, we addressed this challenge by introducing a "meta-pathway" structure that integrated the advantages of the Simple Interaction Format (SIF) while accommodating reaction information. Nevertheless, the earlier Global Integrative Network (GIN) was limited to reliance on KEGG alone. Here, we present GIN version 2.0, which incorporates human molecular interaction data from ten distinct knowledge bases, including KEGG, Reactome, and HumanCyc, among others. We standardized the data structure, gene IDs, and chemical IDs, and conducted a comprehensive analysis of the consistency among the ten knowledge bases before combining all unified interactions into GINv2.0. Utilizing GINv2.0, we investigated the glycolysis process and its regulatory proteins, revealing coordinated regulations on glycolysis and autophagy, particularly under glucose starvation. The expanded scope and enhanced capabilities of GINv2.0 provide a valuable resource for comprehensive systems-level analyses in the field of biological research. GINv2.0 can be accessed at: https://github.com/BIGchix/GINv2.0. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of periprosthetic joint infection (PJI) in the early postoperative period remains a challenge. Although studies have established that serum C-reactive protein (CRP) and synovial markers may be useful, recent studies have suggested that the current thresholds used may lack sensitivity. The purpose of this study was to examine the role of serum CRP, erythrocyte sedimentation rate (ESR), synovial fluid white blood-cell (WBC) count, and polymorphonuclear neutrophil (PMN) percentage in the diagnosis of acute postoperative PJI and to identify the optimal threshold.Methods: This multicenter study included patients who were investigated for possible PJI within 90 days of an index arthroplasty. This study included 197 patients from 4 institutions who underwent total joint arthroplasty from 2000 to 2017. Of these patients, 123 were confirmed to have PJI, and 74 were ruled out as not having PJI (non-infected group). Analyses of receiver operating characteristic (ROC) curves and the area under the curve were performed to determine the value of each test and optimal cutoff values.Results: The optimal cutoff value was 6,130 cells/μL for synovial fluid WBC count (91% sensitivity and 83% specificity), 39.8 mg/L for serum CRP (91% sensitivity and 87% specificity), 39.5 mm/hr for ESR (76% sensitivity and 67% specificity), and 79.5% for PMN percentage (95% sensitivity and 59% specificity). Reducing the acute period from 90 days to 30 days or 45 days made little difference in most threshold values. However, the optimal cutoff for synovial fluid WBC count was almost twice as high (10,170 cells/μL) when using a 30-day definition instead of a 90-day definition.Conclusions: The calculated cutoffs in our study were substantially lower than the thresholds used by the Musculoskeletal Infection Society. The calculated values of this study should be used, as previous cutoffs may be too high and lack sensitivity. In addition, it appears that the threshold values, at least for some of the tests, change as the duration since the index arthroplasty lengthens. A continuum of threshold values that is dependent on the number of days since the index arthroplasty may need to be used for the diagnosis of acute PJI.Level Of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

How states and great powers rise and fall is an intriguing enigma of human history. Are there any patterns? Do polities become more vulnerable over time as they age? We analyze longevity in hundreds of premodern states using survival analysis to help provide initial insights into these questions. This approach is commonly used to study the risk of death in biological organisms or failure in mechanical systems. The results reveal that the risk of state termination increased steeply over approximately the first two centuries after formation and stabilized thereafter. This provides the first quantitative support for the hypothesis that the resilience of political states decreases over time. Potential mechanisms that could drive such declining resilience include environmental degradation, increasing complexity, growing inequality, and extractive institutions. While the cases are from premodern times, such dynamics and drivers of vulnerability may remain relevant today. [ABSTRACT FROM AUTHOR]

Background: The preoperative diagnosis of periprosthetic joint infection (PJI) depends on a series of blood biomarkers. Previous studies have shown that CD64 expression on blood neutrophils and monocytes has a good diagnostic efficacy for diagnosing systemic and local infections. The purpose of the present study was to investigate the role of blood CD64 in the diagnosis of PJI.Methods: On the basis of estimations made before the study was performed, 62 patients were recruited for joint revision surgery following the failure of primary hip or knee replacement. Venous blood was obtained within 24 hours after patient admission, and flow cytometry was performed to evaluate the CD64 expression of 3 groups of white blood cells (WBCs). CD64 expression was measured as CD64 mean fluorescence intensity (CD64MFI). The neutrophil CD64 index (nCD64 index; neutrophil CD64MFI [nCD64MFI]/lymphocyte CD64MFI [lCD64MFI]) and monocyte CD64 index (mCD64 index; monocyte CD64MFI [mCD64MFI]/lCD64MFI) were then calculated. The C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) at admission, synovial fluid indicators, leukocyte esterase test results, intraoperative histological results, and tissue or synovial fluid culture results were recorded. According to the modified Musculoskeletal Infection Society (MSIS) criteria, patients were divided into the PJI group and the non-PJI group. These blood indicators were then analyzed for the diagnosis of PJI.Results: The PJI group included 18 patients, and the non-PJI group included 44 patients. The diagnostic value of the area under the receiver operating characteristic curve (AUC) was low for lCD64MFI, the nCD64 index, and the mCD64 index. The diagnostic value for nCD64MFI was moderate, with an AUC of 0.735 (95% confidence interval [CI], 0.595 to 0.874; p = 0.004). The diagnostic value for mCD64MFI was high, with an AUC of 0.898 (95% CI, 0.821 to 0.975; p < 0.001). The cutoff value for mCD64MFI was 28,968, with a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 1, 0.75, 0.62, and 1, respectively. This result was confirmed by internal validation with a different antibody.Conclusions: Flow cytometry can be used for patient screening before revision surgery, and blood mCD64MFI is a promising indicator for PJI.Level Of Evidence: Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

A green cognitive radio that is solely powered by an energy harvester which extracts energy from the RF signal of a primary user transmitter is considered. The cognitive radio operates in a harvesting-transmitting fashion with the period of one time slot. In each period, it first harvests energy for a fixed duration and then transmits data using the harvested energy for the rest of the period. Considering the intrinsic harvestingthroughput tradeoff, we optimise the harvesting ratio of the cognitive radio to maximise its achievable throughput, subject to the interference constraint by the primary user receiver. It is shown that the formulated optimisation problem is convex and we derive a closed-form expression for the optimal harvesting ratio. Simulations validate the correctness and analyse the achievable throughput and optimal harvesting ratio under different parameters. [ABSTRACT FROM AUTHOR]

Interfacial coupling in hybrid magnetic heterostructures is being considered as a unique opportunity for functional material design. Here, we present the temperature dependence of magnetic properties of V2O3/Co bilayers influenced by the structural phase transition that is accompanied by a metal–insulator transition in V2O3. Both the coercivity and the magnetization of Co layer are strongly affected by the interfacial stress due to the magnetostrictive effect in the ferromagnetic film. The observed change in coercivity is as large as 59% in a narrow temperature range. The changes in the magnetic properties are reproducible and reversible, which are of importance for potential applications. [ABSTRACT FROM AUTHOR]

Representation learning-based recommendation models play a dominant role among recommendation techniques. However, most of the existing methods assume both historical interactions and embedding dimensions are independent of each other, and thus regrettably ignore the high-order interaction information among historical interactions and embedding dimensions. In this article, we propose a novel representation learning-based model called COMET (COnvolutional diMEnsion inTeraction), which simultaneously models the high-order interaction patterns among historical interactions and embedding dimensions. To be specific, COMET stacks the embeddings of historical interactions horizontally at first, which results in two "embedding maps". In this way, internal interactions and dimensional interactions can be exploited by convolutional neural networks (CNN) with kernels of different sizes simultaneously. A fully connected multi-layer perceptron (MLP) is then applied to obtain two interaction vectors. Lastly, the representations of users and items are enriched by the learnt interaction vectors, which can further be used to produce the final prediction. Extensive experiments and ablation studies on various public implicit feedback datasets clearly demonstrate the effectiveness and rationality of our proposed method. [ABSTRACT FROM AUTHOR]

The effect of thermal stress on the growth of central cracks in inhomogeneous cylindrical superconductors is investigated assuming that the material properties vary linearly with the radial coordinate and temperature differences. General expressions for the temperature distribution and thermal stress in terms of a Bessel equation and the plane strain approach are derived. The results indicate that the distributions and variations in the radial and hoop thermal stresses in an inhomogeneous superconductor differ from those in homogeneous superconductors. However, thermal stress affects the crack growth similarly in both superconductor types. The thermal-stress analysis should be useful for the crack growth prediction regarding inhomogeneous superconductors. [ABSTRACT FROM AUTHOR]

Phase-filling singularities in the optical response function of highly doped (>1019cm-3) germanium are theoretically predicted and experimentally confirmed using spectroscopic ellipsometry. Contrary to direct-gap semiconductors, which display the well-known Burstein-Moss phenomenology upon doping, the critical point in the joint density of electronic states associated with the partially filled conduction band in n -Ge corresponds to the so-called E1 and E 1+1 transitions, which are two-dimensional in character. As a result of this reduced dimensionality, there is no edge shift induced by Pauli blocking. Instead, one observes the "original" critical point (shifted only by band gap renormalization) and an additional feature associated with the level occupation discontinuity at the Fermi level. The experimental observation of this feature is made possible by the recent development of low-temperature, in situ doping techniques that allow the fabrication of highly doped films with exceptionally flat doping profiles. [ABSTRACT FROM AUTHOR]

The coherent population trapping (CPT) phenomenon has found widespread application in quantum precision measurements. Various designs based on the narrow resonant spectrum corresponding to the linear Zeeman effect have been demonstrated to achieve high performance. In this article, the nonlinear Zeeman split of the CPT spectrum of 87Rb in the lin ∥ lin setup is investigated. We observe re-split phenomenon for both magnetic sensitive and magnetic insensitive CPT resonant lines at a large magnetic field. The re-split in the magnetic sensitive lines raises a practical problem to magnetometers worked in the lin ∥ lin setup while the other one shows a good potential for applications in large magnetic field. We propose a design based on the nonlinear split of the magnetic insensitive lines and test its performance. It provides a much larger measurement range compared to the linear one, offering an option for atomic magnetometers where a large dynamic range is preferred. [ABSTRACT FROM AUTHOR]

The article focuses on the self-organized mud cracking process in a "Red Beach" salt marsh in China and its role in enhancing ecosystem resilience. Topics include the facilitation of plant establishment and growth through seed trapping and increased water infiltration, the ability of mud cracks to help the salt marsh withstand intense droughts, and the overall importance of physical self-organization in ecosystem dynamics and resilience to climate change.