bluuebunny/crossref_metadata_2025_split huggingface dataset:
Food tax policies in Pacific Island Countries and Territories: systematic policy review
Authors: Walby Emilee , Jones Amanda C , Smith Moira , Na’ati Elisiva , Snowdon Wendy , Teng Andrea M 
Published: December 2023

Abstract

Objective:
To systematically identify and review food taxation policy changes in Pacific Island Countries and Territories (PICTs).

Design:
Food taxation polices, regarding excise taxes and tariffs applied from 2000 to 2020 in twenty-two PICTs, and their key characteristics were reviewed. The search was conducted using databases, government legal repositories and broad-based search engines. Identified documents for screening included legislation, reports, academic literature, news articles and grey literature. Key informants were contacted from each PICT to retrieve further data and confirm results. Results were analysed by narrative synthesis.

Setting:
Noncommunicable diseases (NCD) are the leading cause of premature death in PICTs and in many jurisdictions globally. An NCD crisis has been declared in the Pacific, and food taxation policy has been recommended to address the dietary risk factors associated with. Progress is unclear.

Results:
Of the twenty-two PICTs included in the study, fourteen had food taxation policies and five introduced excise taxes. Processed foods, sugar and salt were the main target of excise taxes. A total of eighty-four food taxation policy changes were identified across all food groups. There was a total of 279 taxes identified by food group, of which 85 % were tariffs and 15 % were excise taxes. Individual tax rates varied substantially. The predominant tax design was ad valorem, and this was followed by volumetric.

Conclusions:
A quarter of PICTs have introduced food excise taxes from 2000 to 2020. Further excise taxes, specifically tiered or nutrient-specific designs, could be introduced and more systematically applied to a broader range of unhealthy foods.
A Latin American Third Way? Juan José Arévalo's Spiritual Socialism, 1916–1963
Authors: Friedman Max Paul 
Published: December 2023

AbstractScholars and US officials mocked Juan José Arévalo Bermejo, the first democratically elected president of Guatemala (1945–51), for the opacity and alleged incoherence of his “spiritual socialism.” He was eclipsed by his successor, Jacobo Árbenz Guzmán, who introduced sweeping land reform to Guatemala and whose overthrow in a CIA-orchestrated coup in 1954 launched the Latin American Cold War. But Arévalo's ideology is not only decipherable but potentially of great value—when we trace its origins back to Karl Christian Friedrich Krause, a forgotten philosopher who was Hegel's contemporary, and the Argentine intellectuals who developed Krause's abstract theories into an approach to governance that shaped Argentina's experience in social democracy under Hipólito Yrigoyen, while Arévalo was living in exile there. Arévalo's social reforms, which improved the standard of living for workers and peasants without sacrificing individual liberties or property rights, reflect a Krausean philosophical commitment to harmonious nationalism based on ethical relationships rather than hierarchies. The experiment was foreclosed by the 1954 coup and a lesser known, US-backed coup in 1963 that denied Arévalo a second term in office. This analysis of Arévalo's writings and governing practices shows their relevance to Latin America's search for a third way between revolutionary class struggle and neoliberal authoritarianism.
Very long chain fatty acid–inhibiting herbicides: Current uses, site of action, herbicide-resistant weeds, and future
Authors: Jhala Amit J. , Singh Mandeep , Shergill Lovreet , Singh Rishabh , Jugulam Mithila , Riechers Dean E. , Ganie Zahoor A. , Selby Thomas P. , Werle Rodrigo , Norsworthy Jason K. 
Published: December 2023

Abstract
The herbicides that inhibit very-long-chain fatty acid (VLCFA) elongases are primarily used for residual weed control in corn, barley, oat, sorghum, soybean, sugarcane, certain vegetable crops, and wheat production fields in the United States. They act primarily by inhibiting shoot development of susceptible species, preventing weed emergence and growth. The objectives of this review were to summarize 1) the chemical family of VLCFA-inhibiting herbicides and their use in the United States, 2) the VLCFA biosynthesis in plants and their site of action, 3) VLCFA-inhibitor resistant weeds and their mechanism of resistance, and 4) the future of VLCFA-inhibiting herbicides. After their reclassification as Group 15 herbicides to include shoot growth-inhibiting herbicides (Group 8), the VLCFA-inhibiting herbicides are currently represented by eight chemical families (benzofurans, thiocarbamates, α-chloroacetamides, α-oxyacetamides, azolyl-carboxamides, isoxazolines, α-thioacetamides, and oxiranes). On average, VLCFA-inhibiting herbicides are applied once a year to both corn and soybean crops in the United States with acetochlor and S-metolachlor being the most used VLCFA-inhibiting herbicides in corn and soybean production, respectively. The site of action of Group 15 herbicides results from inhibition of the VLCFA synthase, which is encoded by several fatty acid elongase (FAE1)-like genes in VLCFA elongase complex in an endoplasmic reticulum. The VLCFA synthase is a condensing enzyme, and relies on a conserved, reactive cysteinyl sulfur in its active site that performs a nucleophilic attack on either the natural substrate (fatty acyl-CoA) or the herbicide. As of August 2023, 13 weed species have been documented to be resistant to VLCFA inhibitors, including 11 monocot weeds and two dicot weeds (Palmer amaranth and waterhemp). The isoxazolines (pyroxasulfone and fenoxasulfone) are the most recently (2014) discovered VLCFA-inhibiting herbicides. Although the intensity of VLCFA-inhibitor-directed discovery efforts has decreased over the past decade, this biochemical pathway remains a viable mechanistic target for the discovery of herbicide premixes and a valuable component of them.
Perfectionism and Baldness Distress in Men
Authors: Kranz Dirk , Razum Josip , Jankowski Glen S. 
Published: December 2023

Abstract: Introduction: Against the backdrop of increasing body image concerns among men, the present study examined two factors that might underlie men’s baldness distress: rigid perfectionism and anxiety about physical aging. Methods: An international sample of 355 men with varying degrees of baldness and an age range of 19 to 64 years were surveyed. Results: As hypothesized, participants scoring high in rigid perfectionism showed higher levels of baldness distress. This association was partially mediated by anxiety about physical aging. The mediation was not further moderated by participants’ age, degree and duration of baldness, cultural context, or racial identity, which underlines the generalizability of results. Discussion and Conclusion: The discussion centers around the partial rather than complete mediation by aging anxiety and implications of the findings for supporting balding men in the public health domain.
Multi‐Layer Evolution of Acoustic‐Gravity Waves and Ionospheric Disturbances Over the United States After the 2022 Hunga Tonga Volcano Eruption
Authors: Inchin P. A. , Bhatt A. , Cummer S. A. , Eckermann S. D. , Harding B. J. , Kuhl D. D. , Ma J. , Makela J. J. , Sabatini R. , Snively J. B. 
Published: December 2023

AbstractThe Hunga‐Tonga Hunga‐Ha'apai volcano underwent a series of large‐magnitude eruptions that generated broad spectra of mechanical waves in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic‐gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano‐induced AGWs in mesopause and ionosphere‐thermosphere airglow imagery and Fabry‐Perot interferometry. We also report unique AGW signatures in the ionospheric D‐region, measured using Long‐Range Navigation pulsed low‐frequency transmitter signals. Although we observed fluctuations over a wide range of periods and speeds, we identify Lamb wave modes exhibiting 295–345 m s−1 phase front velocities with correlated spatial variability of their amplitudes from the Earth's surface to the ionosphere. Results suggest that the Lamb wave modes, tracked by our ray‐tracing modeling results, were accompanied by deep fluctuation fields coupled throughout the atmosphere, and were all largely consistent in arrival times with the sequence of eruptions over 8 hr. The ray results also highlight the importance of winds in reducing wave amplitudes at CONUS midlatitudes. The ability to identify and interpret Lamb wave modes and accompanying fluctuations on the basis of arrival times and speeds, despite complexity in their spectra and modulations by the inhomogeneous atmosphere, suggests opportunities for analysis and modeling to understand their signals to constrain features of hazardous events.
Evidence for Magnetic Reconnection as the Precursor to Discrete Aurora at Mars
Authors: Bowers C. F. , DiBraccio G. A. , Slavin J. A. , Johnston B. , Schneider N. M. , Brain D. A. , Azari A. 
Published: December 2023

AbstractDiscrete aurora at Mars are characterized as localized, short‐lasting ultraviolet emissions on the nightside. They are caused by the precipitation of accelerated electron along open magnetic field lines and their collision with the Martian atmosphere. Discrete auroral emissions detected by the Imaging Ultraviolet Spectrograph (IUVS) instrument onboard the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft occur most frequently over the strongest crustal magnetic anomalies at Mars and under particular local time and upstream interplanetary magnetic field (IMF) conditions. These trends suggest that the onset of discrete aurora is controlled by the processes that govern the interaction between the draped IMF and the crustal magnetic anomalies. Here, we analyze MAVEN magnetometer measurements over regions of strong crustal fields during 49 discrete auroral events observed by IUVS. Our results indicate that the draped IMF orientations during each discrete auroral event show a clear tendency to be anti‐parallel to the underlying crustal anomaly magnetic fields near the location of the emission onset. This suggests that magnetic reconnection, a process that favors anti‐parallel magnetic field regimes, between the crustal fields and the draped IMF plays a role in discrete aurora formation. Of the 49 discrete auroral events analyzed, 42 (86%) occurred under draped IMF conditions that are susceptible to reconnection with the underlying crustal anomalies. This investigation produces strong evidence linking discrete aurora to magnetic reconnection at Mars and provides insights into other trends in discrete auroral activation such as local time and upstream IMF conditions.
Spatial Composition of the Diahaline Overturning Circulation in a Fjord–Type, Non–Tidal Estuarine System
Authors: Henell Erika , Burchard Hans , Gräwe Ulf , Klingbeil Knut 
Published: December 2023

AbstractIn this study we present new insights into the overturning circulation in non‐tidal, fjord‐type estuarine systems associated with diahaline mixing. As a realistic example we analyze 2 years of numerical model results for the Baltic Sea, a brackish semi‐enclosed marginal sea, characterized by strong freshwater surplus. An isohaline water mass transformation framework is applied to quantify and decompose the diahaline exchange flow. Time‐averaged effective vertical diahaline velocity is directly calculated from the divergence of the transports below the respective isohaline surface. It is furthermore indirectly estimated from the gradient of local mixing per salinity class with respect to salinity. Under the assumption of negligible horizontal diffusive salt transports both estimates should be identical. Our analysis shows a high correlation between the spatial patterns of the two estimates for the diahaline exchange flow. Two dominant types of diahaline exchange flow are analyzed. First of all there is a large scale overturning circulation with inflow at places where the isohaline surface is close to the bottom and with outflow at places where the isohaline is surfacing. Secondly, there is the well‐known small‐scale overturning circulation localized inside the bottom boundary layer over sloping bathymetry, associated with boundary mixing. Both types of circulation are visualized across selected vertical transects in physical and in salinity space. One major result is that about 50% of the diahaline exchange flow patterns are generated by numerical mixing caused by the truncation error of the advection scheme, despite the fact that an anti‐diffusive advection scheme and vertically adaptive coordinates are used.
Identifying Structural Priors in a Hybrid Differentiable Model for Stream Water Temperature Modeling
Authors: Rahmani Farshid , Appling Alison , Feng Dapeng , Lawson Kathryn , Shen Chaopeng 
Published: December 2023

AbstractAlthough deep learning models for stream temperature (Ts) have recently shown exceptional accuracy, they have limited interpretability and cannot output untrained variables. With hybrid differentiable models, neural networks (NNs) can be connected to physically based equations (called structural priors) to output intermediate variables such as water source fractions (specifying what portion of water is groundwater, subsurface, and surface flow). However, it is unclear if such outputs are physically meaningful when only limited physics is imposed, and if structural priors have enough impacts to be identifiable from data. Here, we tested four alternative structural priors describing basin‐scale water temperature memory and instream heat processes in a differentiable stream temperature model where NNs freely estimate the water source fractions. We evaluated models’ abilities to predict Ts and baseflow ratio. The four priors exhibited noticeably different behaviors in these two metrics and their tradeoffs, with some dominating others. Therefore, the better structural priors can be identified. Moreover, testing different priors yielded valuable insights: having a separate shallow subsurface flow component better matches observations, and a recency‐weighted averaging of past air temperature for calculating source water temperature resulted in better Ts and baseflow prediction than traditionally employed simple averaging. However, we also highlight the limitations when insufficient physical constraints are implemented: the internal variables (water source fractions) may not be adequately constrained by a single target variable (stream temperature) alone. To ensure the physical significance of the internal fluxes, one can either employ multivariate data for model selection, or include more physical processes in the priors.
A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors
Authors: Wang Kunfeng , Xiong XingYin , Wang Zheng , Ma Liangbo , Wang BoWen , Yang WuHao , Bie Xiaorui , Li ZhiTian , Zou XuDong 
Published: December 2023

AbstractThe development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and resolution. Mode-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance, providing a promising solution to overcome the limitations of traditional sensing technologies. Amplitude noise plays a key role in determining the resolution of mode-localized sensors, as the output metric is derived from the measured AR (amplitude ratio) within the weakly coupled resonator system. However, the amplitude noise originating from the weakly coupled resonator’s closed-loop circuit has not yet been fully investigated. This paper presents a decouple-decomposition (DD) noise analysis model, which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop circuit. The DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the resonators. By integrating the decoupled weakly coupled resonators, the model decomposes the weakly coupled resonator’s closed-loop circuit into distinct paths for amplitude and phase noise analyses. The DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled resonators. MATLAB/Simulink simulations verify the model’s accuracy when compared to theoretical analysis. At the optimal operating point, the mode-localized tilt sensor achieves an input-referred instability of 3.91 × 10-4°and an input-referred AR of PSD of 2.01 × 10-4°⁄√Hz using the closed-loop noise model. This model is also applicable to other varieties of mode-localized sensors.
Mechanisms of PANoptosis and relevant small-molecule compounds for fighting diseases
Authors: Wang Lian , Zhu Yanghui , Zhang Lu , Guo Linghong , Wang Xiaoyun , Pan Zhaoping , Jiang Xian , Wu Fengbo , He Gu 
Published: December 2023

AbstractPyroptosis, apoptosis, and necroptosis are mainly programmed cell death (PCD) pathways for host defense and homeostasis. PANoptosis is a newly distinct inflammatory PCD pathway that is uniquely regulated by multifaceted PANoptosome complexes and highlights significant crosstalk and coordination among pyroptosis (P), apoptosis (A), and/or necroptosis(N). Although some studies have focused on the possible role of PANpoptosis in diseases, the pathogenesis of PANoptosis is complex and underestimated. Furthermore, the progress of PANoptosis and related agonists or inhibitors in disorders has not yet been thoroughly discussed. In this perspective, we provide perspectives on PANoptosome and PANoptosis in the context of diverse pathological conditions and human diseases. The treatment targeting on PANoptosis is also summarized. In conclusion, PANoptosis is involved in plenty of disorders including but not limited to microbial infections, cancers, acute lung injury/acute respiratory distress syndrome (ALI/ARDS), ischemia-reperfusion, and organic failure. PANoptosis seems to be a double-edged sword in diverse conditions, as PANoptosis induces a negative impact on treatment and prognosis in disorders like COVID-19 and ALI/ARDS, while PANoptosis provides host protection from HSV1 or Francisella novicida infection, and kills cancer cells and suppresses tumor growth in colorectal cancer, adrenocortical carcinoma, and other cancers. Compounds and endogenous molecules focused on PANoptosis are promising therapeutic strategies, which can act on PANoptosomes-associated members to regulate PANoptosis. More researches on PANoptosis are needed to better understand the pathology of human conditions and develop better treatment.
A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation
Authors: Tomaszkiewicz Karolina , Owerko Tomasz 
Published: December 2023

AbstractMonitoring of structures’ condition plays a fundamental role in providing safety for users and extending the structures’ lifespan. The monitoring is conducted through on-site inspections by engineers thus this process is time-consuming, labor-intensive and prone to subjective engineering opinions. Detecting damage using machine learning algorithms on images can support engineers’ work, especially for early damages which are difficult to see with the human eye. This article is focused on the concrete crack detection problem in engineering structural elements. Despite the availability of several concrete crack detection datasets, no dataset allows semantic segmentation of cracks narrower than 0.3 mm (the crack width limit for typical engineering structures elements and environmental conditions according to EC 1992-1-1) and the ability for crack classification is limited. The provided open dataset represents only cracks below the crack width limit of 0.3mm, which do not yet indicate concrete elements failure. It is dedicated for early crack classification and segmentation, so that damage protection can be taken at an early stage to prevent structural element damages.
A chromosome-scale assembly of the early-flowering Prunus campanulata and comparative genomics of cherries
Authors: Hu Yuxi , Feng Chao , Wu Baohuan , Kang Ming 
Published: December 2023

AbstractPrunus campanulata is an important flowering cherry germplasm of high ornamental value. Given its early-flowering phenotypes, P. campanulata could be used for molecular breeding of ornamental species and fruit crops belonging to the subgenus Cerasus. Here, we report a chromosome-scale assembly of P. campanulata with a genome size of 282.6 Mb and a contig N50 length of 12.04 Mb. The genome contained 24,861 protein-coding genes, of which 24,749 genes (99.5%) were functionally annotated, and 148.20 Mb (52.4%) of the assembled sequences are repetitive sequences. A combination of genomic and population genomic analyses revealed a number of genes under positive selection or accelerated molecular evolution in P. campanulata. Our study provides a reliable genome resource, and lays a solid foundation for genetic improvement of flowering cherry germplasm.
Physics constrained unsupervised deep learning for rapid, high resolution scanning coherent diffraction reconstruction
Authors: Hoidn Oliver , Mishra Aashwin Ananda , Mehta Apurva 
Published: December 2023

AbstractBy circumventing the resolution limitations of optics, coherent diffractive imaging (CDI) and ptychography are making their way into scientific fields ranging from X-ray imaging to astronomy. Yet, the need for time consuming iterative phase recovery hampers real-time imaging. While supervised deep learning strategies have increased reconstruction speed, they sacrifice image quality. Furthermore, these methods’ demand for extensive labeled training data is experimentally burdensome. Here, we propose an unsupervised physics-informed neural network reconstruction method, PtychoPINN, that retains the factor of 100-to-1000 speedup of deep learning-based reconstruction while improving reconstruction quality by combining the diffraction forward map with real-space constraints from overlapping measurements. In particular, PtychoPINN gains a factor of 4 in linear resolution and an 8 dB improvement in PSNR while also accruing improvements in generalizability and robustness. This blend of performance and computational efficiency offers exciting prospects for high-resolution real-time imaging in high-throughput environments such as X-ray free electron lasers (XFELs) and diffraction-limited light sources.