bluuebunny/crossref_metadata_2025 huggingface dataset:
The Court as Concert Hall: Music at the U.S. Supreme Court
Authors: Doering James M. , Bell Lauren C.
Published: March 2023

The U.S. Supreme Court has for decades served as an unlikely venue for the performance of music. Between 1988 and 2020, more than 125 musicians, including some of the country's most prominent performers, appeared for intimate audiences in the Supreme Court's East Conference Room. The concerts were officially “off the record,” but details survive in records kept by the U.S. Supreme Court, papers of former justices and friends of the court involved in the creation of the programs, and in interviews with individuals who supported and participated in the events. This article reconstructs the history of this long running but little-known music series and contextualizes it within the court's culture and broader themes of access and power.
Discrimination of weeds from sugarcane in Louisiana using hyperspectral leaf reflectance data and pigment analysis
Authors: Johnson Richard M. , Orgeron Albert J. , Spaunhorst Douglas J. , Huang I-Shuo , Zimba Paul V.
Published: March 2023

Controlling weeds is a critically important task in sugarcane production systems. Weeds compete for light, nutrients, and water, and if they are not managed properly can negatively impact sugarcane yields. Accurate detection of weeds versus desired plants was assessed using hyperspectral and pigment analyses. Leaf samples were collected from four commercial Louisiana sugarcane varieties, and nine weed species commonly found in sugarcane fields. Hyperspectral leaf reflectance data (350 to 850 nm) were collected from all samples. Plant pigment (chlorophylls and carotenoids) levels were also determined using high-performance liquid chromatography, and concentrations were determined using authentic standards and leaf area. In all cases, leaf reflectance data successfully differentiated sugarcane from weeds using canonical discrimination analysis. Linear discriminant analysis showed that the accuracy of the classification varied from 67% to 100% for individual sugarcane varieties and weed species. In all cases, sugarcane was not misclassified as a weed. Plant pigment levels exhibited marked differences between sugarcane varieties and weed species with differences in chlorophyll and carotenoid explaining much of the observed variation in reflectance. The ratio of chlorophyll a to chlorophyll b showed significant differences between sugarcane and all weed species. The successful implementation of this technology as either an airborne system to scout and map weeds or a tractor-based system to identify and spray weeds in real-time would offer sugarcane growers a valuable tool for managing their crops. By accurately targeting weeds in sugarcane fields that are emerged and growing, the total amount of herbicide applied could be decreased, resulting in cost savings for the grower and reduced environmental impacts.
Long‐Term Variation of the Quasi‐Five‐Day Wave in the Top Layer of Venus Clouds
Authors: Lai Dexin , Li Tao
Published: March 2023

Planetary waves play an essential role in the momentum budget of Venus's atmosphere superrotation. Using the Longwave Infrared Camera (LIR) observations of the Akatsuki and their cloud‐tracking wind fields, we study the characteristics of planetary waves and their long‐term variations. The dominant planetary wave is a wavenumber 1 wave with a period of 5–6 days (Quasi‐Five‐Day wave or QFDW) and is symmetrically distributed in the midlatitudes of both hemispheres. The wave phase speed is close to the background zonal wind, indicating the possible existence of a critical level near the LIR emission altitude of 65 km. The QFDW tends to appear at ∼8:00 a.m. local time, suggesting a modulation by the thermal tide. The QFDW amplitude is correlated with the vertical shear of the background zonal wind modulated by the thermal tide. This indicates some nonlinear interaction between the thermal tide and the QFDW.
Global Surface Ocean Acidification Indicators From 1750 to 2100
Authors: Jiang Li‐Qing , Dunne John , Carter Brendan R. , Tjiputra Jerry F. , Terhaar Jens , Sharp Jonathan D. , Olsen Are , Alin Simone , Bakker Dorothee C. E. , Feely Richard A. , Gattuso Jean‐Pierre , Hogan Patrick , Ilyina Tatiana , Lange Nico , Lauvset Siv K. , Lewis Ernie R. , Lovato Tomas , Palmieri Julien , Santana‐Falcón Yeray , Schwinger Jörg , Séférian Roland , Strand Gary , Swart Neil , Tanhua Toste , Tsujino Hiroyuki , Wanninkhof Rik , Watanabe Michio , Yamamoto Akitomo , Ziehn Tilo
Published: March 2023

Accurately predicting future ocean acidification (OA) conditions is crucial for advancing OA research at regional and global scales, and guiding society's mitigation and adaptation efforts. This study presents a new model‐data fusion product covering 10 global surface OA indicators based on 14 Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), along with three recent observational ocean carbon data products. The indicators include fugacity of carbon dioxide, pH on total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content. The evolution of these OA indicators is presented on a global surface ocean 1° × 1° grid as decadal averages every 10 years from preindustrial conditions (1750), through historical conditions (1850–2010), and to five future Shared Socioeconomic Pathways (2020–2100): SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. These OA trajectories represent an improvement over previous OA data products with respect to data quantity, spatial and temporal coverage, diversity of the underlying data and model simulations, and the provided SSPs. The generated data product offers a state‐of‐the‐art research and management tool for the 21st century under the combined stressors of global climate change and ocean acidification. The gridded data product is available in NetCDF at the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0259391.html, and global maps of these indicators are available in jpeg at: https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/surface-oa-indicators.html.
Metabolic surgery-induced changes of the growth hormone system relate to improved adipose tissue function
Authors: Gancheva Sofiya , Kahl Sabine , Herder Christian , Strassburger Klaus , Sarabhai Theresia , Pafili Kalliopi , Szendroedi Julia , Schlensak Matthias , Roden Michael
Published: March 2023

Aims

Body weight loss improves insulin resistance and growth hormone secretion in obesity, which may be regulated by leptin according to preclinical studies. How changes in leptin, lipids and insulin sensitivity after bariatric (metabolic) surgery affect the human growth hormone system is yet unclear.

Participants and methods

People with obesity (OBE, n = 79, BMI 50.8 ± 6.3 kg/m2) were studied before, 2, 12, 24 and 52 weeks after metabolic surgery and compared to lean healthy humans (control; CON, n = 24, BMI 24.3 ± 3.1 kg/m2). Tissue-specific insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamps with D-[6,6-2H2]glucose. Fasting leptin, growth hormone (GH), insulin-like growth factor 1 (IGF-1) and IGF-binding proteins (IGFBP1, IGFBP3) were measured using ELISA.

Results

At baseline, OBE exhibited higher glycemia and leptinemia as well as pronounced peripheral, adipose tissue and hepatic insulin resistance compared to CON. GH and IGFBP1 were lower, while IGF1 was comparable between groups. At 52 weeks, OBE had lost 33% body weight and doubled their peripheral insulin sensitivity, which was paralleled by continuous increases in GH, IGF-1 and IGFBP1 as well as decrease in leptin. The rise in GH correlated with reductions in free fatty acids, adipose tissue insulin resistance and insulinemia, but not with changes in body weight, peripheral insulin sensitivity, glycemia or leptinemia. The rise in IGF-1 correlated with reduction in high-sensitive C-reactive protein.

Conclusion

Reversal of alterations of the GH-IGF-1 axis after surgically-induced weight loss is unlikely related to improved leptin secretion and/or insulin sensitivity, but is rather associated with restored adipose tissue function and reduced low-grade inflammation.
A tip-coupled, two-cantilever, non-resonant microsystem for direct measurement of liquid viscosity
Authors: Tiwari Sudhanshu , Dangi Ajay , Pratap Rudra
Published: March 2023

We report a non-resonant piezoelectric microelectromechanical cantilever system for the measurement of liquid viscosity. The system consists of two PiezoMEMS cantilevers in-line, with their free ends facing each other. The system is immersed in the fluid under test for viscosity measurement. One of the cantilevers is actuated using the embedded piezoelectric thin film to oscillate at a pre-selected non-resonant frequency. The second cantilever, the passive one, starts to oscillate due to the fluid-mediated energy transfer. The relative response of the passive cantilever is used as the metric for the fluid’s kinematic viscosity. The fabricated cantilevers are tested as viscosity sensors by carrying out experiments in fluids with different viscosities. The viscometer can measure viscosity at a single frequency of choice, and hence some important considerations for frequency selection are discussed. A discussion on the energy coupling between the active and the passive cantilevers is presented. The novel PiezoMEMS viscometer architecture proposed in this work will overcome several challenges faced by state-of-the-art resonance MEMS viscometers, by enabling faster and direct measurement, straightforward calibration, and the possibility of shear rate-dependent viscosity measurement.
Multimodal MEMS vibration energy harvester with cascaded flexible and silicon beams for ultralow frequency response
Authors: Feng Haizhao , Bu Ling , Li Zhangshanhao , Xu Sixing , Hu Bingmeng , Xu Minghao , Jiang Siyao , Wang Xiaohong
Published: March 2023

Scavenged energy from ambient vibrations has become a promising energy supply for autonomous microsystems. However, restricted by device size, most MEMS vibration energy harvesters have much higher resonant frequencies than environmental vibrations, which reduces scavenged power and limits practical applicability. Herein, we propose a MEMS multimodal vibration energy harvester with specifically cascaded flexible PDMS and “zigzag” silicon beams to simultaneously lower the resonant frequency to the ultralow-frequency level and broaden the bandwidth. A two-stage architecture is designed, in which the primary subsystem consists of suspended PDMS beams characterized by a low Young’s modulus, and the secondary system consists of zigzag silicon beams. We also propose a PDMS lift-off process to fabricate the suspended flexible beams and the compatible microfabrication method shows high yield and good repeatability. The fabricated MEMS energy harvester can operate at ultralow resonant frequencies of 3 and 23 Hz, with an NPD index of 1.73 μW/cm3/g2 @ 3 Hz. The factors underlying output power degradation in the low-frequency range and potential enhancement strategies are discussed. This work offers new insights into achieving MEMS-scale energy harvesting with ultralow frequency response.
Probing neural circuit mechanisms in Alzheimer’s disease using novel technologies
Authors: Grieco Steven F. , Holmes Todd C. , Xu Xiangmin
Published: March 2023

The study of Alzheimer’s Disease (AD) has traditionally focused on neuropathological mechanisms that has guided therapies that attenuate neuropathological features. A new direction is emerging in AD research that focuses on the progressive loss of cognitive function due to disrupted neural circuit mechanisms. Evidence from humans and animal models of AD show that dysregulated circuits initiate a cascade of pathological events that culminate in functional loss of learning, memory, and other aspects of cognition. Recent progress in single-cell, spatial, and circuit omics informs this circuit-focused approach by determining the identities, locations, and circuitry of the specific cells affected by AD. Recently developed neuroscience tools allow for precise access to cell type-specific circuitry so that their functional roles in AD-related cognitive deficits and disease progression can be tested. An integrated systems-level understanding of AD-associated neural circuit mechanisms requires new multimodal and multi-scale interrogations that longitudinally measure and/or manipulate the ensemble properties of specific molecularly-defined neuron populations first susceptible to AD. These newly developed technological and conceptual advances present new opportunities for studying and treating circuits vulnerable in AD and represent the beginning of a new era for circuit-based AD research.
Mucin glycans drive oral microbial community composition and function
Authors: Wu Chloe M. , Wheeler Kelsey M. , Cárcamo-Oyarce Gerardo , Aoki Kazuhiro , McShane Abigail , Datta Sujit S. , Mark Welch Jessica L. , Tiemeyer Michael , Griffen Ann L. , Ribbeck Katharina
Published: March 2023

Human microbiome composition is closely tied to health, but how the host manages its microbial inhabitants remains unclear. One important, but understudied, factor is the natural host environment: mucus, which contains gel-forming glycoproteins (mucins) that display hundreds of glycan structures with potential regulatory function. Leveraging a tractable culture-based system to study how mucins influence oral microbial communities, we found that mucin glycans enable the coexistence of diverse microbes, while resisting disease-associated compositional shifts. Mucins from tissues with unique glycosylation differentially tuned microbial composition, as did isolated mucin glycan libraries, uncovering the importance of specific glycan patterns in microbiome modulation. We found that mucins shape microbial communities in several ways: serving as nutrients to support metabolic diversity, organizing spatial structure through reduced aggregation, and possibly limiting antagonism between competing taxa. Overall, this work identifies mucin glycans as a natural host mechanism and potential therapeutic intervention to maintain healthy microbial communities.
The potential to produce tropodithietic acid by Phaeobacter inhibens affects the assembly of microbial biofilm communities in natural seawater
Authors: Bech Pernille Kjersgaard , Zhang Sheng-Da , Henriksen Nathalie Nina Suhr Eiris , Bentzon-Tilia Mikkel , Strube Mikael Lenz , Gram Lone
Published: March 2023

Microbial secondary metabolites play important roles in biotic interactions in microbial communities and yet, we do not understand how these compounds impact the assembly and development of microbial communities. To address the implications of microbial secondary metabolite production on biotic interactions in the assembly of natural seawater microbiomes, we constructed a model system where the assembly of a natural seawater biofilm community was influenced by the addition of the marine biofilm forming Phaeobacter inhibens that can produce the antibiotic secondary metabolite tropodithietic acid (TDA), or a mutant incapable of TDA production. Because of the broad antibiotic activity of TDA, we hypothesized that the potential of P. inhibens to produce TDA would strongly affect both biofilm and planktonic community assembly patterns. We show that 1.9 % of the microbial composition variance across both environments could be attributed to the presence of WT P. inhibens, and especially genera of the Bacteriodetes were increased by the presence of the TDA producer. Moreover, network analysis with inferred putative microbial interactions revealed that P. inhibens mainly displayed strong positive associations with genera of the Flavobacteriaceae and Alteromonadaceae, and that P. inhibens acts as a keystone OTU in the biofilm exclusively due to its potential to produce TDA. Our results demonstrate the potential impact of microbial secondary metabolites on microbial interactions and assembly dynamics of complex microbial communities.
Attosecond magnetization dynamics in non-magnetic materials driven by intense femtosecond lasers
Authors: Neufeld Ofer , Tancogne-Dejean Nicolas , De Giovannini Umberto , Hübener Hannes , Rubio Angel
Published: March 2023

Irradiating solids with ultrashort laser pulses is known to initiate femtosecond timescale magnetization dynamics. However, sub-femtosecond spin dynamics have not yet been observed or predicted. Here, we explore ultrafast light-driven spin dynamics in a highly nonresonant strong-field regime. Through state-of-the-art ab initio calculations, we predict that a nonmagnetic material can transiently transform into a magnetic one via dynamical extremely nonlinear spin-flipping processes, which occur on attosecond timescales and are mediated by cascaded multi-photon and spin–orbit interactions. These are nonperturbative nonresonant analogs to the inverse Faraday effect, allowing the magnetization to evolve in very high harmonics of the laser frequency (e.g. here up to the 42nd, oscillating at ~100 attoseconds), and providing control over the speed of magnetization by tuning the laser power and wavelength. Remarkably, we show that even for linearly polarized driving, where one does not intuitively expect the onset of an induced magnetization, the magnetization transiently oscillates as the system interacts with light. This response is enabled by transverse light-driven currents in the solid, and typically occurs on timescales of ~500 attoseconds (with the slower femtosecond response suppressed). An experimental setup capable of measuring these dynamics through pump–probe transient absorption spectroscopy is simulated. Our results pave the way for attosecond regimes of manipulation of magnetism.
Co-option of epidermal cells enables touch sensing
Authors: Mangione Federica , Titlow Joshua , Maclachlan Catherine , Gho Michel , Davis Ilan , Collinson Lucy , Tapon Nicolas
Published: March 2023

The epidermis is equipped with specialized mechanosensory organs that enable the detection of tactile stimuli. Here, by examining the differentiation of the tactile bristles, mechanosensory organs decorating the Drosophila adult epidermis, we show that neighbouring epidermal cells are essential for touch perception. Each mechanosensory bristle signals to the surrounding epidermis to co-opt a single epidermal cell, which we named the F-Cell. Once specified, the F-Cell adopts a specialized morphology to ensheath each bristle. Functional assays reveal that adult mechanosensory bristles require association with the epidermal F-Cell for touch sensing. Our findings underscore the importance of resident epidermal cells in the assembly of functional touch-sensitive organs.
ATG7 and ATG14 restrict cytosolic and phagosomal Mycobacterium tuberculosis replication in human macrophages
Authors: Aylan Beren , Bernard Elliott M. , Pellegrino Enrica , Botella Laure , Fearns Antony , Athanasiadi Natalia , Bussi Claudio , Santucci Pierre , Gutierrez Maximiliano G.
Published: March 2023

Autophagy is a cellular innate-immune defence mechanism against intracellular microorganisms, including Mycobacterium tuberculosis (Mtb). How canonical and non-canonical autophagy function to control Mtb infection in phagosomes and the cytosol remains unresolved. Macrophages are the main host cell in humans for Mtb. Here we studied the contributions of canonical and non-canonical autophagy in the genetically tractable human induced pluripotent stem cell-derived macrophages (iPSDM), using a set of Mtb mutants generated in the same genetic background of the common lab strain H37Rv. We monitored replication of Mtb mutants that are either unable to trigger canonical autophagy (Mtb ΔesxBA) or reportedly unable to block non-canonical autophagy (Mtb ΔcpsA) in iPSDM lacking either ATG7 or ATG14 using single-cell high-content imaging. We report that deletion of ATG7 by CRISPR–Cas9 in iPSDM resulted in increased replication of wild-type Mtb but not of Mtb ΔesxBA or Mtb ΔcpsA. We show that deletion of ATG14 resulted in increased replication of both Mtb wild type and the mutant Mtb ΔesxBA. Using Mtb reporters and quantitative imaging, we identified a role for ATG14 in regulating fusion of phagosomes containing Mtb with lysosomes, thereby enabling intracellular bacteria restriction. We conclude that ATG7 and ATG14 are both required for restricting Mtb replication in human macrophages.
Global detection of human variants and isoforms by deep proteome sequencing
Authors: Sinitcyn Pavel , Richards Alicia L. , Weatheritt Robert J. , Brademan Dain R. , Marx Harald , Shishkova Evgenia , Meyer Jesse G. , Hebert Alexander S. , Westphall Michael S. , Blencowe Benjamin J. , Cox Jürgen , Coon Joshua J.
Published: March 2023

An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual proteins are typically identified by peptide sequences representing a small fraction of their total amino acids. Hence, an average shotgun experiment fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery of protein isoforms. Using six different human cell lines, six proteases, deep fractionation and three tandem mass spectrometry fragmentation methods, we identify a million unique peptides from 17,717 protein groups, with a median sequence coverage of approximately 80%. Direct comparison with RNA expression data provides evidence for the translation of most nonsynonymous variants. We have also hypothesized that undetected variants likely arise from mutation-induced protein instability. We further observe comparable detection rates for exon–exon junction peptides representing constitutive and alternative splicing events. Our dataset represents a resource for proteoform discovery and provides direct evidence that most frame-preserving alternatively spliced isoforms are translated.
Panoramic visual statistics shape retina-wide organization of receptive fields
Authors: Gupta Divyansh , Młynarski Wiktor , Sumser Anton , Symonova Olga , Svatoň Jan , Joesch Maximilian
Published: March 2023

Statistics of natural scenes are not uniform—their structure varies dramatically from ground to sky. It remains unknown whether these nonuniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. Using the mouse (Mus musculus) as a model species, we show that receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon, in agreement with our predictions. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell types.
A multi-sensor dataset with annotated activities of daily living recorded in a residential setting
Authors: Tonkin Emma L. , Holmes Michael , Song Hao , Twomey Niall , Diethe Tom , Kull Meelis , Perello Nieto Miquel , Camplani Massimo , Hannuna Sion , Fafoutis Xenofon , Zhu Ni , Woznowski Przemysław R. , Tourte Gregory J. L. , Santos-Rodríguez Raúl , Flach Peter A. , Craddock Ian
Published: March 2023

SPHERE is a large multidisciplinary project to research and develop a sensor network to facilitate home healthcare by activity monitoring, specifically towards activities of daily living. It aims to use the latest technologies in low powered sensors, internet of things, machine learning and automated decision making to provide benefits to patients and clinicians. This dataset comprises data collected from a SPHERE sensor network deployment during a set of experiments conducted in the ‘SPHERE House’ in Bristol, UK, during 2016, including video tracking, accelerometer and environmental sensor data obtained by volunteers undertaking both scripted and non-scripted activities of daily living in a domestic residence. Trained annotators provided ground-truth labels annotating posture, ambulation, activity and location. This dataset is a valuable resource both within and outside the machine learning community, particularly in developing and evaluating algorithms for identifying activities of daily living from multi-modal sensor data in real-world environments. A subset of this dataset was released as a machine learning competition in association with the European Conference on Machine Learning (ECML-PKDD 2016).
HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy
Authors: Ehrenfeld Alejandro , Egaña Álvaro F. , Santibañez-Leal Felipe , Garrido Felipe , Ojeda Marcia , Townley Brian , Navarro Felipe
Published: March 2023

Supervised analysis using spectral data requires a well-informed characterisation of the response variables and abundant spectral data points. The presented hyperspectral dataset comes from five sets of geometallurgical samples, each characterised by different methods. To provide the spectral data, all mineral samples were scanned with SPECIM VNIR and SWIR hyperspectral cameras. For each subset the following data are provided 1) hyperspectral reflectance images in the VNIR spectral range (400–1000 nm wavelength); 2) hyperspectral reflectance images in the SWIR spectral range (900–2500 nm wavelength); 3) hyperspectral reflectance images in the VNIR-SWIR range (merged to SWIR spatial resolution); 4) RGB images constructed from hyperspectral data using a Bilateral Filter based sensor fusion method; 5) response variables representing mineral sample characterisation results, provided as training and validation data. This dataset is intended for use in general regression and classification research and experiments. All subsets were validated using machine learning models with satisfactory results.
The risk assessment of rockburst intensity in the highway tunnel based on the variable fuzzy sets theory
Authors: Wang Ai-Feng , Yang Xiu-Tao , Gu Xin-Bao
Published: March 2023

Rockbursts have important influences on construction safety, so the risk assessment of rockburst intensity has great significance. Firstly, the depth of the rockburst, the uniaxial compressive strength, the stress concentration coefficients, the brittleness coefficients, and the elastic energy index are selected as the evaluation index. Secondly, an assessment model is developed based on the fuzzy variable theory. And the model is proposed to assess the rockburst intensity in the highway tunnel. Finally, the results demonstrate that the results derived from the proposed model are consistent with the current specifications; the accurate rate comes to 100%. The method can determine the risk level of rockburst intensity and provide an alternative scheme. Hence, the study can accurately present a new approach to assess the rockburst intensity in the future.
Climate warming and increasing Vibrio vulnificus infections in North America
Authors: Archer Elizabeth J. , Baker-Austin Craig , Osborn Timothy J. , Jones Natalia R. , Martínez-Urtaza Jaime , Trinanes Joaquín , Oliver James D. , González Felipe J. Colón , Lake Iain R.
Published: March 2023

Vibrio vulnificus is an opportunistic bacterial pathogen, occurring in warm low-salinity waters. V. vulnificus wound infections due to seawater exposure are infrequent but mortality rates are high (~ 18%). Seawater bacterial concentrations are increasing but changing disease pattern assessments or climate change projections are rare. Here, using a 30-year database of V. vulnificus cases for the Eastern USA, changing disease distribution was assessed. An ecological niche model was developed, trained and validated to identify links to oceanographic and climate data. This model was used to predict future disease distribution using data simulated by seven Global Climate Models (GCMs) which belong to the newest Coupled Model Intercomparison Project (CMIP6). Risk was estimated by calculating the total population within 200 km of the disease distribution. Predictions were generated for different “pathways” of global socioeconomic development which incorporate projections of greenhouse gas emissions and demographic change. In Eastern USA between 1988 and 2018, V. vulnificus wound infections increased eightfold (10–80 cases p.a.) and the northern case limit shifted northwards 48 km p.a. By 2041–2060, V. vulnificus infections may expand their current range to encompass major population centres around New York (40.7°N). Combined with a growing and increasingly elderly population, annual case numbers may double. By 2081–2100 V. vulnificus infections may be present in every Eastern USA State under medium-to-high future emissions and warming. The projected expansion of V. vulnificus wound infections stresses the need for increased individual and public health awareness in these areas.
A hierarchical dynamic Bayesian learning network for EMG-based early prediction of voluntary movement intention
Authors: Chen Yongming , Zhang Haihong , Wang Chuanchu , Ang Kai Keng , Ng Soon Huat , Jin Huiwen , Lin Zhiping
Published: March 2023

Decoding human action intention prior to motion onset with surface electromyograms (sEMG) is an emerging neuroengineering topic with interesting clinical applications such as intelligent control of powered prosthesis/exoskeleton devices. Despite extensive prior works in the related fields, it remains a technical challenge due to considerable variability of complex multi-muscle activation patterns in terms of volatile spatio-temporal characteristics. To address this issue, we first hypothesize that the inherent variability of theidlestate immediately preceding the motion initiation needs to be addressed explicitly. We therefore design a hierarchical dynamic Bayesian learning network model that integrates an array of Gaussian mixture model – hidden Markov models (GMM-HMMs), where each GMM-HMM learns the multi-sEMG processes either during the idle state, or during the motion initiation phase of a particular motion task. To test the hypothesis and evaluate the new learning network, we design and build a upper-limb sEMG-joystick motion study system, and collect data from 11 healthy volunteers. The data collection protocol adapted from the psychomotor vigilance task includes repeated and randomized binary hand motion tasks (push or pull) starting from either of two designatedidlestates: relaxed (with minimal muscle tones), or prepared (with muscle tones). We run a series of cross-validation tests to examine the performance of the method in comparison with the conventional techniques. The results suggest that the idle state recognition favors the dynamic Bayesian model over a static classification model. The results also show a statistically significant improvement in motion prediction accuracy by the proposed method (93.83±6.41%) in comparison with the conventional GMM-HMM method (89.71±8.98%) that does not explicitly account for the idle state. Moreover, we examine the progress of prediction accuracy over the course of motion initiation and identify the important hidden states that warrant future research.
Impact of reactivity controlled compression ignition (RCCI) mode engine operation in diesel engine powered with B20 blend of waste cooking oil biodiesel
Authors: Anish M. , Jayaprabakar J. , Bency P. , Joy Nivin , Jayaprakash V. , Arunkumar K. , Aravind Kumar J. , Praveenkumar T. R. , Ghfar Ayman A. , Rajasimman M. , Ravindran Balasubramani
Published: March 2023

The purpose of this study is to conduct an experimental assessment of the impact of RCCI (reactivity regulated compression ignition) on the performance, emissions, and combustion of a CRDI engine. A fuel mix (20% biodiesel, 80% diesel, and a NaOH catalyst) is generated. The produced combination is evaluated for attributes using standards established by the American Society for Testing and Materials (ASTM). The engine research included three distinct kinds of injections: 10% Pen RCCI, 20% Pen RCCI, and 30% Pen RCCI. Increasing the injection pressure increases the brake thermal efficiency, often known as BTE. NOx emissions increased as a consequence of higher injection pressures and improved combustion. However, when the injection rate is increased, the Specific Fuel Consumption (SFC) falls. The CO2 and hydrocarbon emissions, as well as the smoke opacity values, increased as the charge increased. The resultant mixture may be utilized in a CI engine with pre-mixed ignition to improve overall engine performance as well as combustion characteristics.
Longitudinal changes in disgust sensitivity during pregnancy and the early postpartum period, and the role of recent health problems
Authors: Dlouhá Daniela , Roberts S. Craig , Hlaváčová Jana , Nouzová Kamila , Kaňková Šárka
Published: March 2023

Disgust is an essential part of the behavioral immune system, protecting the individual from infection. According to the Compensatory Prophylaxis Hypothesis (CPH), disgust sensitivity increases in times of immunosuppression, potentially including pregnancy. We aimed to replicate a previous study observing longitudinal changes in disgust sensitivity in pregnant women. Additionally, for the first time, we explored how recent health problems influence these changes. To do this, we obtained disgust sensitivity measures from 94 women in each trimester and in early postpartum. In contrast to the original study, where disgust sensitivity was highest in the first trimester, we found that overall and animal reminder disgust increased across pregnancy and after birth. In line with the CPH, women who were recently sick in the first trimester had elevated disgust sensitivity at that time. Although disgust sensitivity was significantly higher in the second trimester and postpartum period compared to the first trimester in mothers pregnant with a male fetus, the overall results regarding the effect of fetus sex on disgust sensitivity were mixed. It seems that changing levels of disgust sensitivity during pregnancy and postpartum result from a suite of physiological and psychological changes that occur during this sensitive period of a woman’s life.
Universal scaling laws and density slopes for dark matter haloes
Authors: Xu Zhijie
Published: March 2023

Smalls scale challenges suggest some missing pieces in our current understanding of dark matter. A cascade theory for dark matter is proposed to provide extra insights, similar to the cascade phenomenon in hydrodynamic turbulence. The kinetic energy is cascaded in dark matter from small to large scales involves a constant rate $$\varepsilon _u$$

ε
u

($$\approx -\,4.6\times 10^{-7}{\text { m}}^2/{\text { s}}^3$$

≈
-

4.6
×

10

-
7

m

2

/

s

3

). Confirmed by N-body simulations, the energy cascade leads to a two-thirds law for kinetic energy $$v_r^2$$

v
r
2

on scale r such that $$v_r^2 \propto (\varepsilon _u r)^{2/3}$$

v
r
2

∝

(

ε
u

r
)

2
/
3

. Equivalently, a four-thirds law can be established for mean halo density $$\rho _s$$

ρ
s

enclosed in the scale radius $$r_s$$

r
s

such that $$\rho _s \propto \varepsilon _u^{2/3}G^{-1}r_s^{-4/3}$$

ρ
s

∝

ε
u

2
/
3

G

-
1

r
s

-
4
/
3

, which was confirmed by galaxy rotation curves. Critical properties of dark matter might be obtained by identifying key constants on relevant scales. First, the largest halo scale $$r_l$$

r
l

can be determined by $$-u_0^3/\varepsilon _u$$

-

u
0
3

/

ε
u

, where $$u_0$$

u
0

is the velocity dispersion. Second, the smallest scale $$r_{\eta }$$

r
η

is dependent on the nature of dark matter. For collisionless dark matter, $$r_{\eta } \propto (-{G\hbar /\varepsilon _{u}}) ^{1/3}\approx 10^{-13}\,{\text {m}}$$

r
η

∝

(
-

G
ħ
/

ε
u

)

1
/
3

≈

10

-
13

m

, where $$\hbar$$
ħ
is the Planck constant. An uncertainty principle for momentum and acceleration fluctuations is also postulated. For self-interacting dark matter, $$r_{\eta } \propto \varepsilon _{u}^2 G^{-3}(\sigma /{{m}})^3$$

r
η

∝

ε

u

2

G

-
3

(
σ
/
m
)

3

, where $$\sigma /m$$

σ
/
m

is the cross-section of interaction. On halo scale, the energy cascade leads to an asymptotic density slope $$\gamma =-\,4/3$$

γ
=
-

4
/
3

for fully virialized haloes with a vanishing radial flow, which might explain the nearly universal halo density. Based on the continuity equation, halo density is analytically shown to be closely dependent on the radial flow and mass accretion, such that simulated haloes can have different limiting slopes. A modified Einasto density profile is proposed accordingly.
Advancing neutron diffraction for accurate structural measurement of light elements at megabar pressures
Authors: Haberl Bianca , Guthrie Malcolm , Boehler Reinhard
Published: March 2023

Over the last 60 years, the diamond anvil cell (DAC) has emerged as the tool of choice in high pressure science because materials can be studied at megabar pressures using X-ray and spectroscopic probes. In contrast, the pressure range for neutron diffraction has been limited due to low neutron flux even at the strongest sources and the resulting large sample sizes. Here, we introduce a neutron DAC that enables break-out of the previously limited pressure range. Key elements are ball-bearing guides for improved mechanical stability, gem-quality synthetic diamonds with novel anvil support and improved in-seat collimation. We demonstrate a pressure record of 1.15 Mbar and crystallographic analysis at 1 Mbar on the example of nickel. Additionally, insights into the phase behavior of graphite to 0.5 Mbar are described. These technical and analytical developments will further allow structural studies on low-Z materials that are difficult to characterize by X-rays.
A polygenic and family risk score are both independently associated with risk of type 2 diabetes in a population-based study
Authors: Duschek Elena , Forer Lukas , Schönherr Sebastian , Gieger Christian , Peters Annette , Kronenberg Florian , Grallert Harald , Lamina Claudia
Published: March 2023

The availability of polygenic scores for type 2 diabetes (T2D) raises the question, whether assessing family history might become redundant. However, family history not only involves shared genetics, but also shared environment. It was the aim of this study to assess the independent and combined effects of one family risk score (FamRS) and a polygenic score (PGS) on prevalent and incident T2D risk in a population-based study from Germany (n = 3071). The study was conducted in 2004/2005 with up to 12 years of follow-up. The FamRS takes into account not only the number of diseased first grade relatives, but also age at onset of the relatives and age of participants. 256 prevalent and additional 163 incident T2D cases were recorded. Prevalence of T2D increased sharply for those within the top quantile of the PGS distribution resulting in an OR of 19.16 (p < 2 × 10–16) for the top 20% compared to the remainder of the population, independent of age, sex, BMI, physical activity and FamRS. On the other hand, having a very strong family risk compared to average was still associated with an OR of 2.78 (p = 0.001), independent of the aforementioned factors and the PGS. The PGS and FamRS were only slightly correlated (r2Spearman = 0.018). The combined contribution of both factors varied with varying age-groups, though, with decreasing influence of the PGS with increasing age. To conclude, both, genetic information and family history are relevant for the prediction of T2D risk and might be used for identification of high risk groups to personalize prevention measures.
Characterization of radiation-resistance mechanism in Spirosoma montaniterrae DY10T in terms of transcriptional regulatory system
Authors: Cho Changyun , Lee Dohoon , Jeong Dabin , Kim Sun , Kim Myung Kyum , Srinivasan Sathiyaraj
Published: March 2023

To respond to the external environmental changes for survival, bacteria regulates expression of a number of genes including transcription factors (TFs). To characterize complex biological phenomena, a biological system-level approach is necessary. Here we utilized six computational biology methods to infer regulatory network and to characterize underlying biologically mechanisms relevant to radiation-resistance. In particular, we inferred gene regulatory network (GRN) and operons of radiation-resistance bacterium Spirosoma montaniterrae DY10$$^T$$

T

and identified the major regulators for radiation-resistance. Our results showed that DNA repair and reactive oxygen species (ROS) scavenging mechanisms are key processes and Crp/Fnr family transcriptional regulator works as a master regulatory TF in early response to radiation.
Predicting choice behaviour in economic games using gaze data encoded as scanpath images
Authors: Byrne Sean Anthony , Reynolds Adam Peter Frederick , Biliotti Carolina , Bargagli-Stoffi Falco J. , Polonio Luca , Riccaboni Massimo
Published: March 2023

Eye movement data has been extensively utilized by researchers interested in studying decision-making within the strategic setting of economic games. In this paper, we demonstrate that both deep learning and support vector machine classification methods are able to accurately identify participants’ decision strategies before they commit to action while playing games. Our approach focuses on creating scanpath images that best capture the dynamics of a participant’s gaze behaviour in a way that is meaningful for predictions to the machine learning models. Our results demonstrate a higher classification accuracy by 18% points compared to a baseline logistic regression model, which is traditionally used to analyse gaze data recorded during economic games. In a broader context, we aim to illustrate the potential for eye-tracking data to create information asymmetries in strategic environments in favour of those who collect and process the data. These information asymmetries could become especially relevant as eye-tracking is expected to become more widespread in user applications, with the seemingly imminent mass adoption of virtual reality systems and the development of devices with the ability to record eye movement outside of a laboratory setting.
Solution proposal for completed preference structure in ORESTE method
Authors: Yerlikaya Mehmet Akif , Yildiz Kürşat , Keskin Büşra Nur
Published: March 2023

In this study, a novel integrated method including CRITIC (Criteria Importance Through Inter-Criteria Correlation) and ORESTE (Organisation, Rangement Et Synth&e De DonnCes Relarionnelles) methods from MCDM (multi-criteria decision making) methods and aiming to solve the problem of inconsistency in the ORESTE method has been proposed. Since the ORESTE method only considers the ordering of alternatives and criteria, a conflict may occur due to the different ordering of each alternative in the criteria. To solve the conflict problem in the second step of the ORESTE method, it is proposed to create the preference density matrix of the alternatives by using the CRITIC weights of the criteria, and to calculate the net flow values with reference to the PROMETHEE II (Preference Ranking Organization Method for Encrichment Evaluations II) method (C-ORESTE III). The CRITIC method is used because the relationship between the criteria is as important as the alternatives in calculating the normalized preference intensities. To test the validity and applicability of the proposed method, an application is made to the logistics center location problem within the scope of green logistics.
An effective technique for developing the graphical polynomials of certain molecular graphs
Authors: Masmali Ibtisam , Nadeem Muhammad , Yousaf Awais , Akbar Ali , Razaq Abdul , Razzaque Asima
Published: March 2023

Counting Polynomial is the mathematical function that was initially introduced for application in chemistry in 1936 by G. Polya. Partitioning of graphs can be seen in the coefficients of these mathematical functions, which also reveal the frequency with which these partitions happen. We developed a novel and efficient method for constructing the necessary counting polynomials for a zigzag-edge coronoid formed by the fusion of a Starphene graph and a Kekulenes graph. The study's methods expand our knowledge, and its findings potentially provide insight on the topology of these chemical structures.
Socioeconomic and education-based inequality in suspected developmental delays among Nepalese children: a subnational level assessment
Authors: Acharya Kiran , Rahman Md. Shafiur , Islam Md. Rashedul , Gilmour Stuart , Dhungel Bibha , Parajuli Rajendra P. , Nishimura Tomoko , Senju Atsushi , Tsuchiya Kenji J.
Published: March 2023

Failure to meet early childhood developmental milestones leads to difficulty in schooling and social functioning. Evidence on the inequality in the burden of developmental delays across population groups, and identification of potential risk factors for suspected developmental delays (SDD) among younger children, are essential for designing appropriate policies and programs. This study explored the level of socioeconomic and maternal education-based inequality in the prevalence of SDD among Nepalese children at subnational level and identified potential risk factors. Individual-level data from the 2019 Nepal Multiple Indicator Cluster Survey was used to estimate the prevalence of SDD among children aged 3–4 years. Regression-based slope index of inequality (SII) and relative index of inequality were used to measure the magnitude of inequality, in terms of household socioeconomic status (SES) and mother’s education, in the prevalence of SDD. In addition, a multilevel logistic regression model was used to identify potential risk factors for SDD. The national prevalence of SDD was found to be 34.8%, with relatively higher prevalence among children from rural areas (40.0%) and those from Karnali Province (45.0%) followed by Madhesh province (44.2%), and Sudhurpashchim Province (40.1%). The prevalence of SDD was 32 percentage points higher (SII: −0.32) among children from the poorest households compared to their rich counterparts at the national level. At the subnational level, such inequality was found to be highest in Lumbini Province (SII = −0.47) followed by Karnali Province (SII = −0.37), and Bagmati Province (SII = −0.37). The prevalence of SDD was 36 percentage points higher (SII: −0.36) among children whose mother had no formal education compared to children of higher educated mothers. The magnitude of education-based absolute inequality in SDD was highest in Lumbini Province (SII = −0.44). Multilevel logistic regression model identified lower levels of mother’s education, disadvantaged SES and childhood stunting as significant risk factors for SDD. One in each three children in Nepal may experience SDD, with relatively higher prevalence among children from rural areas. Subnational level variation in prevalence, and socioeconomic and education-based inequality in SDD highlight the urgent need for province-specific tailored interventions to promote early childhood development in Nepal.