Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil legacy nutrients contribute to the decreasing stoichiometric ratio of N and P loading from the Mississippi River Basin

Human‐induced nitrogen–phosphorus (N, P) imbalance in terrestrial ecosystems can lead to disproportionate N and P loading to aquatic ecosystems, subsequently shifting the elemental ratio in estuaries and coastal oceans and impacting both the structure and functioning of aquatic ecosystems. The N:P ratio of nutrient loading to the Gulf of Mexico from the Mississippi River Basin increased before the late 1980s driven by the enhanced usage of N fertilizer over P fertilizer, whereafter the N:P loading ratio started to decrease although the N:P ratio of fertilizer application did not exhibit a similar trend. Here, we hypothesize that different release rates of soil legacy nutrients might contribute to the decreasing N:P loading ratio. Our study used a data‐model integration framework to evaluate N and P dynamics and the potential for long‐term accumulation or release of internal soil nutrient legacy stores to alter the ratio of N and P transported down the rivers. We show that the longer residence time of P in terrestrial ecosystems results in a much slower release of P to coastal oceans than N. If contemporary nutrient sources were reduced or suspended, P loading sustained by soil legacy P would decrease much slower than that of N, causing a decrease in the N and P loading ratio. The longer residence time of P in terrestrial ecosystems and the increasingly important role of soil legacy nutrients as a loading source may explain the decreasing N:P loading ratio in the Mississippi River Basin. Our study underscores a promising prospect for N loading control and the urgency to integrate soil P legacy into sustainable nutrient management strategies for aquatic ecosystem health and water security.
Potential biopsychosocial factors mediating/moderating the relationship between depressive symptoms and body size among children and adolescents: A systematic review

The prevalence of depression and obesity in the pediatric population has increased along with multiple adverse health outcomes in later life. However, the mechanisms underlying the bidirectional relationship between obesity and depression have not yet been clarified. We aim to systematically summarize the literature reporting on mediational or moderational biopsychosocial factors in the relationship between depression and body size among children and adolescents. Four electronic databases (PubMed, Web of Science, PsycINFO, and PsychArticles) were systematically searched from inception until December 23, 2021, and subsequently updated until June 9, 2023. The study protocol was registered with PROSPERO (CRD42022301475). A total of 36 unique records reporting 152,513 children and adolescents meeting the inclusion criteria were identified. The results indicate that disparate psychological variables (e.g., body image, victimization and bullying, eating disorders, and sleep problems) may mediate the bidirectional relationship between depressive symptoms and body size. Moreover, the mediational/moderational effect of biological factors has not been well established. The moderational effect of social factors was inconsistently reported. Future research should aim to identify and characterize factors that may impact the bidirectional relationship between depression and obesity to inform prevention intervention strategies for affected children and adolescents.
Transient Flow to a Large‐Diameter Well in an Aquifer With Storative Semiconfining Layers

The Hantush theory of leaky aquifers with storge in the semiconfining layers is combined with large-diameter well theory to produce equations that can be used in the analysis of pumped-well and observation well data for stratified formations. Included in the equations are storage in the pumped well and a linear resistance to flow at the sand face or well bore skin. Three cases proposed by Hantush are considered. These depend upon whether the upper boundary of the overlying semiconfining layer or the lower boundary of the underlying semiconfining layer are constant head or no-flow boundaries. Laplace transform solutions, valid for the complete time domain, are given for each of the three cases for the hydraulic head in the pumped well, the aquifer, and each of the semiconfining layers. Type cures obtained by numerical inversion are selected to illustrate the effects of well bore storage, well bore skin, and leakage. Although several dimensionless parameters are involved, these parameters tend to influence the character of different portions of the type curves, suggesting that unique matches are possible. The type curves show that well bore storage in a large-diameter well may completely obliterate effects of leakage derived from compressible storage in semiconfining layers. For the purposes of aquifer testing, it may be possible to reduce the magnitude of well bore storage in a large-diameter well and thus reveal the presence of leaky semiconfining layers. This may help to prevent erroneous interpretation of the well test data and incorrect evaluation of the aquifer parameters.
Use of clinical variables for preoperative prediction of lymph node metastasis in endometrial cancer

Abstract Objective Endometrial cancer is the most common gynaecological cancer, and most patients are identified during early disease stages. Noninvasive evaluation of lymph node metastasis likely will improve the quality of clinical treatment, for example, by omitting unnecessary lymphadenectomy. Methods The study population comprised 611 patients with endometrial cancer who underwent lymphadenectomy at four types of institutions, comprising seven hospitals in total. We systematically assessed the association of 18 preoperative clinical variables with postoperative lymph node metastasis. We then constructed statistical models for preoperative lymph node metastasis prediction and assessed their performance with a previously proposed system, in which the score was determined by counting the number of high-risk variables among the four predefined ones. Results Of the preoperative 18 variables evaluated, 10 were significantly associated with postoperative lymph node metastasis. A logistic regression model achieved an area under the curve of 0.85 in predicting lymph node metastasis; this value is significantly higher than that from the previous system (area under the curve, 0.74). When we set the false-negative rate to ~1%, the new predictive model increased the rate of true negatives to 21%, compared with 6.8% from the previous one. We also provide a spreadsheet-based tool for further evaluation of its ability to predict lymph node metastasis in endometrial cancer. Conclusions Our new lymph node metastasis prediction method, which was based solely on preoperative clinical variables, performed significantly better than the previous method. Although additional evaluation is necessary for its clinical use, our noninvasive system may help improve the clinical treatment of endometrial cancer, complementing minimally invasive sentinel lymph node biopsy.
Chloro-iodomethane in N. Atlantic waters: A potentially significant source of atmospheric iodine

Measurements have been made of chloroiodomethane (CH2ClI) in seawater samples collected in the N.W. Atlantic. Elevated concentrations (> 3 ng/ L) were found in surface waters at a number of locations in the pelagic zone. Background surface concentrations in the pelagic zone were 0.1–0.4 ng/L. Coastal/shelf regions averaged 0.1 ng/L off Labrador and Greenland, and 0.8 ng/L on the Grand Banks. We suggest that its distribution may be due to a phytoplankton source, either direct or indirect (i.e. via an intermediate compound). Using measurements of methyl iodide (CH3I) made on the same samples, we make a first order estimate of the comparative fluxes of the two compounds from ocean to atmosphere. This indicates that the iodine carried by CH2ClI may be comparable with that carried as CH3I. Refinement of the flux estimates requires measurements of atmospheric concentrations of CH2ClI, and determination of its Henry's Law constant.
The incidence of intraoperatively acquired pressure injuries in the park‐bench position was reduced by applying soft silicone multilayer foam dressings

Abstract The Park‐Bench Position (PBP) is associated with a high incidence rate of intraoperatively acquired pressure injuries (IAPIs). Preventive measures must be established to prevent the development of IAPIs. We investigated the risk factors for PBP by applying a soft silicone multilayered foam dressing (SMD) under core temperature management to prevent IAPIs. We conducted a prospective, single‐centre, open‐label observational study of patients undergoing elective neurosurgery operations using PBP in a university hospital in Japan. The incidence rate of IAPIs in this study was compared with that in our two previous studies, in which a film dressing was applied and core temperature management was not performed. IAPIs developed in 90 patients (6.7%); in the lateral thoracic region in five patients and the iliac crest region in one patient. The operative time (every 1 h: p = 0.0001, OR: odds ratio 3.62, 95% CI: confidence interval 1.73–11.42) was significantly associated with the incidence of IAPIs. In our two previous studies, the incidence rate of IAPIs was 11.0% and 24.1%, respectively, when film dressing was used. SMD may weaken the involvement of risk factors in IAPIs.
A Low Noise Neural Recording Frontend IC With Power Management for Closed-Loop Brain-Machine Interface Application

Brain-machine Interface (BMI) with implantable bioelectronics systems can provide an alternative way to cure neural diseases, while a power management system plays an important role in providing a stable voltage supply for the implanted chip. a prototype system of power management integrated circuit (PMIC) with heavy load capability supplying artifacts tolerable neural recording integrated circuit (ATNR-IC) is presented in this work. A reverse nested miller compensation (RNMC) low dropout regulator (LDO) with a transient enhancer is proposed for the PMIC. The power consumption is 0.55 mW and 22.5 mW at standby (SB) and full stimulation (ST) load, respectively. For a full load transition, the overshoot and downshoot of the LDO are 110 mV and 71 mV, respectively, which help improve the load transient response during neural stimulation. With the load current peak-to-peak range is about 560 μA supplied by a 4-channel stimulator, the whole PMIC can output a stable 3.3 V supply voltage, which indicates that this PMIC can be extended for more stimulating channels’ scenarios. When the ATNR-IC is supplied for presented PMIC through a voltage divider network, it can amplify the signal consisting of 1 mVpp simulated neural signal and 20 mVpp simulated artifact by 28 dB with no saturation.
The consequences of a local approach in statistical models of convection on its large‐scale coherence

Organized tropical convection is a crucial mechanism in the climate system, but its representation in climate models through parametrization schemes has numerous shortcomings. One of these shortcomings is that they are deterministic despite the statistical nature of the relationship they are representing. Several attempts at devising a stochastic parametrization scheme have been made, many of which assume a local approach, that is, one in which the convection in a grid box is determined without consideration of the previous time steps and the surrounding boxes. This study seeks to explore the effect of this assumption on the coherence of convection using cloud regimes, which represent various modes of tropical convection. First, we analyze the coherence of observed convection beyond the typical size of a model grid box and time step. Then, we evaluate the consequences of the local assumption on this coherence in simple statistical models. Cloud regimes in the real world show high degrees of coherence, manifesting in their lifetimes, areas, and inter‐regime relationships. However, in a local statistical model, they are too small, too short‐lived, and have incorrect relationships between each other. This can be improved by incorporating time memory and spatial dependence in the modeling. Our results imply that a local approach to a statistical representation of convection is not viable, and a statistical model must account for nonlocal influence in order to have large‐scale convective coherence that more closely resembles the real world.
Nonlinear Frequency Mixing Ultrasound Imaging of Nanoscale Contrast Agents

Objective: Nanoscale ultrasound contrast agents show promise as alternatives for diagnostics and therapies due to their enhanced stability and ability to traverse blood vessels. Nonetheless, their reduced size limits echogenicity. This study introduces an enhanced nanobubble frequency mixing ultrasound imaging method, by capitalizing on their nonlinear acoustic response to dual-frequency excitation. Methods: A single broadband transducer (L12-3v) controlled by a programmable ultrasound system was used to transmit a dual-frequency single-cycle wavefront. The frequency mixing effect enabled simultaneous transducer capture of nanobubble-generated sum and difference frequencies in real time without the need for additional hardware or post-processing, by substituting the single-frequency wavefront in a standard contrast harmonic pulse inversion imaging protocol, with the dual-frequency wavefront. Results: Optimization experiments were conducted in tissue mimicking phantoms. Among the dual-frequency combinations that were tested, the highest contrast was obtained using 4&8 MHz. The nanobubble contrast improved with increased mechanical index, and achieved a maximal contrast improvement of 8.4 ± 0.5 dB compared to 4 MHz pulse inversion imaging. In imaging of a breast cancer tumor mouse model, after a systemic nanobubble injection, the contrast was improved by 3.4 ± 1.7, 4.8 ± 1.8, and 6.3 ± 1.6 dB for mechanical indices of 0.04, 0.08, and 0.1, respectively. Conclusion: Nonlinear frequency mixing significantly improved the nanobubble contrast, which facilitated their imaging in-vivo. Significance: This study offers a new avenue to enhance ultrasound imaging utilizing nanobubbles, potentially leading to advancements in other diagnostic applications.
Turnover of Soil Organic Matter under Pasture as Determined by 13C Natural Abundance

The change in vegetation cover from rainforest with a C3 photosynthetic pathway to grasses with C4 pathways was used to follow input rates and turnover of organic matter in a krasnozem over an 83 year period. The measurement of 613c values on soils from three depths (0.0-7.5, 7.5-15.0, 60.0-80.0 cm) indicated that charcoal was a serious contaminant in the light fractions ( 1.6 Mg m-3 fraction from the three depths were calculated as 60, 75 and 276 years respectively, compared with 75, 108 and 348 years for the organic matter within microaggregates from the same horizons. It is concluded that the presence of microaggregates is an important factor in stabilizing organic matter in this soil type. Some difficulties with the technique are also discussed.
Identifying Phage Sequences From Metagenomic Data Using Deep Neural Network With Word Embedding and Attention Mechanism

Phages are the functional viruses that infect bacteria and they play important roles in microbial communities and ecosystems. Phage research has attracted great attention due to the wide applications of phage therapy in treating bacterial infection in recent years. Metagenomics sequencing technique can sequence microbial communities directly from an environmental sample. Identifying phage sequences from metagenomic data is a vital step in the downstream of phage analysis. However, the existing methods for phage identification suffer from some limitations in the utilization of the phage feature for prediction, and therefore their prediction performance still need to be improved further. In this article, we propose a novel deep neural network (called MetaPhaPred) for identifying phages from metagenomic data. In MetaPhaPred, we first use a word embedding technique to encode the metagenomic sequences into word vectors, extracting the latent feature vectors of DNA words. Then, we design a deep neural network with a convolutional neural network (CNN) to capture the feature maps in sequences, and with a bi-directional long short-term memory network (Bi-LSTM) to capture the long-term dependencies between features from both forward and backward directions. The feature map consists of a set of feature patterns, each of which is the weighted feature extracted by a convolution filter with convolution kernels in the CNN slide along the input feature vectors. Next, an attention mechanism is used to enhance contributions of important features. Experimental results on both simulated and real metagenomic data with different lengths demonstrate the superiority of the proposed MetaPhaPred over the state-of-the-art methods in identifying phage sequences.
Observational hints for a plume‐fed, suboceanic asthenosphere and its role in mantle convection

An asthenosphere layer which is entirely fed from below by plumes and which loses equal mass by accretion to the overlying oceanic lithosphere and at subduction zones may play a critical role in shaping the form of mantle convection. In this study we discuss geochemical, seismic, and geoid/depth evidence for lateral flow within this type of asthenosphere. In particular, we suggest that there are large-scale layered, horizontal flow structures that connect upward plume input beneath hotspots to near-ridge regions of increased asthenosphere accretion into the growing oceanic lithosphere. Lateral asthenosphere flow is also shaped by oceanic subduction zones, with a partial return flow from trenches, and by deep continental roots that are migrating barriers to asthenosphere flow. This alternative paradigm offers relatively simple explanations for several puzzles about mantle convection, for example, the low mantle heat flow beneath continents. It also offers an explanation for why mid-ocean ridges appear to be passive features that migrate with little geochemical or morphological change with respect to the lower mantle and seem to be uncoupled from large-scale mantle flow, while in contrast, trenches appear to be strongly coupled to mantle-thick regions of fast (colder) seismic velocity anomalies. We also discuss several implications of this paradigm that should be testable in future studies, such as the prediction of cogenetic off-axis seamount volcanism that is created between an off-axis hotspot and its neighboring ridge axis.
MODELING NONLINEAR ANISOTROPIC ELASTIC PROPERTIES OF UNBOUND GRANULAR BASES USING MICROSTRUCTURE DISTRIBUTION TENSORS

The resilient properties of unbound aggregate bases are important parameters in the design of asphalt pavements. Previous studies have shown that these resilient properties exhibit nonlinear and transverse anisotropic characteristics. This paper presents a micromechanics-based approach to model the nonlinear and anisotropic properties of unbound aggregate bases. The anisotropic behavior is captured using two microstructure parameters representing the preferred orientation of aggregate particles, and the ratio of the normal contact stiffness to shear contact stiffness among particles. The nonlinear response is modeled using a relationship that relates the shear modulus to particle packing, material properties, particle size and confining pressure. The micromechanics model is used to represent resilient properties for a total of 18 different combinations of material conditions with different aggregate types, moisture contents and gradation characteristics. Anisotropic and nonlinear resilient properties were measured at ten different stress states for each of the material conditions. The results presented in this paper show that the micromechanics model is capable of successfully representing the experimental measurements.
Clinical impact of COVID-19 in patients with carbapenem-resistant Acinetobacter baumannii bacteraemia

Abstract The aim of this study was to evaluate the impact of coronavirus disease 2019 (COVID-19) on treatment outcomes in critically ill patients with carbapenem-resistant Acinetobacter baumannii (CRAB) bloodstream infection (BSI). This single-centre, retrospective cohort study was conducted in a 1,048-bed university-affiliated tertiary hospital in the Republic of Korea from January 2021 to March 2022. The study participants included consecutive hospitalised adult patients (aged ≥18 years) in the intensive care unit with CRAB monomicrobial BSI. During the study period, a total of 70 patients were included in our study, and 24 (34.3%) were diagnosed with COVID-19. The 28-day mortality rate was 64.3%. In the multivariate Cox proportional hazard regression analysis, diagnosis of COVID-19 (hazard ratio (HR), 2.91; 95% confidence interval (CI): 1.45–5.87), neutropenia (HR, 2.76; 95% CI: 1.04–7.29), Pitt bacteraemia score (per point; HR, 1.30; 95% CI: 1.19–1.41), and appropriate definite antibiotic therapy (HR, 0.31; 95% CI: 0.15–0.62) were independent predictors of 28-day mortality in patients with CRAB BSI. In conclusion, our findings suggested that COVID-19 has a negative prognostic impact on patients with CRAB BSI. Further study is needed to investigate the specific mechanisms of how COVID-19 worsens the prognosis of CRAB infection.
Impact of Coronavirus Disease–era Clinical Trial Reform on Cancer Trial Access in Rural/Underserved Regions of the Midwest

Objectives: The coronavirus disease 2019 pandemic refocused the cancer community on bringing clinical trials closer to patients and increasing access for traditionally underserved communities. Pandemic-era deregulation increased flexibility with telemedicine visits, less frequent testing, and the ability to have tests done locally. This study evaluates the impact of 2020 cancer clinical trial reform on trial accessibility in rural/underserved regions of the Midwest. Methods: Publicly available clinicaltrials.gov data was accessed from January 1, 2018 to September 30, 2022 for the 3 leading causes of new cancer cases in Kentucky, Tennessee, Illinois, and Indiana. Interventional trials were categorized based on location using corresponding “Rural-Urban Commuting Area” codes (urban/metropolitan, suburban/micropolitan, small town/rural, and isolated/rural) and categorized as pre versus postpandemic (using March 15, 2020, when national regulatory guidelines were modified). Locations of trial offerings from pre and postpandemic dates were analyzed by paired t test. Comparison of trial location category by state and cancer type was analyzed by 1-way analysis of variance with pairwise multiple comparisons made using the Tukey-Kramer method. Results: Pandemic-era deregulation had no impact on increasing trial availability in suburban and small-town/rural locales (P = 0.1259). Only 18% of trials were offered outside of urban areas, with 15% in suburban and 3% in small town/rural areas. Results varied by state (P < 0.0001) with Illinois offering the most suburban and small-town trial availability (27%) compared with Kentucky, Indiana, and Tennessee (18%, 6%, and 2%, respectively). Trial availability in rural versus urban areas did not differ by cancer type (P = 0.07197). Conclusions: More work must be done to increase access to cancer clinical trials in rural and suburban areas of the United States.