The effect of milorganite, a commercially available organic soil amendment, on soil nutrients, plant growth, and yield has been investigated. However, its effect on soil hydraulic properties remains less understood. Therefore, this study aimed to investigate the effect of milorganite amendment on soil evaporation, moisture retention, hydraulic conductivity, and electrical conductivity of a Krome soil. A column experiment was conducted with two milorganite application rates (15 and 30% v/v) and a non-amended control soil. The results revealed that milorganite reduced evaporation rates and the length of Stage I of the evaporation process compared with the control. Moreover, milorganite increased moisture retention at saturation and permanent wilting point while decreasing soil hydraulic conductivity. In addition, milorganite increased soil electrical conductivity. Overall, milorganite resulted in increased soil moisture retention; however, moisture in the soil may not be readily available for plants due to increased soil salinity.

We describe a new low-frequency wideband radio survey of the southern sky. Observations covering 72–231 MHz and Declinations south of $+30^\circ$ have been performed with the Murchison Widefield Array “extended” Phase II configuration over 2018–2020 and will be processed to form data products including continuum and polarisation images and mosaics, multi-frequency catalogues, transient search data, and ionospheric measurements. From a pilot field described in this work, we publish an initial data release covering 1,447 $\mathrm{deg}^2$ over $4\,\mathrm{h}\leq \mathrm{RA}\leq 13\,\mathrm{h}$ , $-32.7^\circ \leq \mathrm{Dec} \leq -20.7^\circ$ . We process twenty frequency bands sampling 72–231 MHz, with a resolution of 2′–45′′, and produce a wideband source-finding image across 170–231 MHz with a root mean square noise of $1.27\pm0.15\,\mathrm{mJy\,beam}^{-1}$ . Source-finding yields 78,967 components, of which 71,320 are fitted spectrally. The catalogue has a completeness of 98% at ${{\sim}}50\,\mathrm{mJy}$ , and a reliability of 98.2% at $5\sigma$ rising to 99.7% at $7\sigma$ . A catalogue is available from Vizier; images are made available via the PASA datastore, AAO Data Central, and SkyView. This is the first in a series of data releases from the GLEAM-X survey.

The enzyme 5,10-methylenetetrahydrofolate reductase (MTHFR) links the folate cycle that produces one-carbon units with the methionine cycle that converts these into S-adenosylmethionine (SAM), the universal methyl donor for almost all methyltransferases. Previously, MTHFR has been shown to be regulated by phosphorylation, which suppresses its activity. SAM levels have been shown to increase substantially soon after initiation of meiotic maturation of the mouse germinal vesicle (GV) stage oocyte and then decrease back to their original low level in mature second meiotic metaphase (MII) eggs. As MTHFR controls the entry of one-carbon units into the methionine cycle, it is a candidate regulator of the SAM levels in oocytes and eggs. Mthfr transcripts are expressed in mouse oocytes and preimplantation embryos and MTHFR protein is present at each stage. In mature MII eggs, the apparent molecular weight of MTHFR was increased compared with GV oocytes, which we hypothesized was due to increased phosphorylation. The increase in apparent molecular weight was reversed by treatment with lambda protein phosphatase (LPP), indicating that MTHFR is phosphorylated in MII eggs. In contrast, LPP had no effect on MTHFR from GV oocytes, 2-cell embryos, or blastocysts. MTHFR was progressively phosphorylated after initiation of meiotic maturation, reaching maximal levels in MII eggs before decreasing again after egg activation. As phosphorylation suppresses MTHFR activity, it is predicted that MTHFR becomes inactive during meiotic maturation and is minimally active in MII eggs, which is consistent with the reported changes in SAM levels during mouse oocyte maturation.

The goal for many PhD students in archaeology is tenure-track employment. Students primarily receive their training by tenure-track or tenured professors, and they are often tacitly expected—or explicitly encouraged—to follow in the footsteps of their advisor. However, the career trajectories that current and recent PhD students follow may hold little resemblance to the ones experienced by their advisors. To understand these different paths and to provide information for current PhD students considering pursuing a career in academia, we surveyed 438 archaeologists holding tenured or tenure-track positions in the United States. The survey, recorded in 2019, posed a variety of questions regarding the personal experiences of individual professors. The results are binned by the decade in which the respondent graduated. Evident patterns are discussed in terms of change over time. The resulting portraits of academic pathways through the past five decades indicate that although broad commonalities exist in the qualifications of early career academics, there is no singular pathway to obtaining tenure-track employment. We highlight the commonalities revealed in our survey to provide a set of general qualifications that might provide a baseline set of skills and experiences for an archaeologist seeking a tenure-track job in the United States.

OBJECTIVES/GOALS: Diffusion basis spectrum imaging (DBSI) allows for detailed evaluation of white matter microstructural changes present in cervical spondylotic myelopathy (CSM). Our goal is to utilize multidimensional clinical and quantitative imaging data to characterize disease severity and predict long-term outcomes in CSM patients undergoing surgery. METHODS/STUDY POPULATION: A single-center prospective cohort study enrolled fifty CSM patients who underwent surgical decompression and twenty healthy controls from 2018-2021. All patients underwent diffusion tensor imaging (DTI), DBSI, and complete clinical evaluations at baseline and 2-years follow-up. Primary outcome measures were the modified Japanese Orthopedic Association score (mild [mJOA 15-17], moderate [mJOA 12-14], severe [mJOA 0-11]) and SF-36 Physical and Mental Component Summaries (PCS and MCS). At 2-years follow-up, improvement was assessed via established MCID thresholds. A supervised machine learning classification model was used to predict treatment outcomes. The highest-performing algorithm was a linear support vector machine. Leave-one-out cross-validation was utilized to test model performance. RESULTS/ANTICIPATED RESULTS: A total of 70 patients – 20 controls, 25 mild, and 25 moderate/severe CSM patients – were enrolled. Baseline clinical and DTI/DBSI measures were significantly different between groups. DBSI Axial and Radial Diffusivity were significantly correlated with baseline mJOA and mJOA recovery, respectively (r=-0.33, p<0.01; r=-0.36, p=0.02). When predicting baseline disease severity (mJOA classification), DTI metrics alone performed with 38.7% accuracy (AUC: 72.2), compared to 95.2% accuracy (AUC: 98.9) with DBSI metrics alone. When predicting improvement after surgery (change in mJOA), clinical variables alone performed with 33.3% accuracy (AUC: 0.40). When combining DTI or DBSI parameters with key clinical covariates, model accuracy improved to 66.7% (AUC: 0.65) and 88.1% (AUC: 0.95) accuracy, respectively. DISCUSSION/SIGNIFICANCE: DBSI metrics correlate with baseline disease severity and outcome measures at 2-years follow-up. Our results suggest that DBSI may serve as a valid non-invasive imaging biomarker for CSM disease severity and potential for postoperative improvement.

OBJECTIVES/GOALS: Approximately 10% of COVID-19 patients experience multiple symptoms weeks and months after the acute phase of infection. Our goal was to use advanced machine learning methods to identify PASC phenotypes based on their symptom profiles, and their association with critical adverse outcomes, with the goal of designing future targeted interventions. METHODS/STUDY POPULATION: Data. All COVID-19 outpatients from 12 University of Minnesota hospitals and 60 clinics. Independent variables consisted of 20 CDC-defined PASC symptoms extracted from clinical notes using NLP. Covariates included demographics, and outcomes included New Psychological Diagnostic Evaluation, and Number of PASC Hospital Visits (>=5). Cases (n=3235) consisted of patients with at least one symptom, and controls (n=3034) consisted of patients with no symptoms. Method. (1) Used bipartite network analysis and modularity maximization to identify patient-symptom biclusters. (2) Used multivariable logistic regression (adjusted for demographics and corrected through Bonferroni) to measure the odds ratio of each patient bicluster to adverse outcomes, compared to controls, and to each of the other biclusters. RESULTS/ANTICIPATED RESULTS: The analysis identified 6 PASC phenotypes (http://www.skbhavnani.com/DIVA/Images/Fig-1-PASC-Network.jpg), which was statistically significant compared to 1000 random permutations of the data (PASC=.31, Random Median=.27, z=11, P<.01). Three of the clusters (Cluster-1, Cluster-4, and Cluster-5 encircled with ovals in Fig. 1) contained CNS-related symptoms, which had statistically significant risk for one or both of the adverse outcomes. For example, Cluster-1 with critical CNS symptoms (depression, insomnia, anxiety, brain-fog/difficulty-thinking), had a significantly higher OR compared to the controls for New Psychological Diagnostic Evaluation (OR=6.6, CI=4.9-9.1, P-corr<.001), in addition to having a significantly higher ORs for the same outcome compared to all the other clusters. DISCUSSION/SIGNIFICANCE: The results identified distinct PASC phenotypes based on symptom profiles, with three of them related to CNS symptoms, each of which had significantly higher risk for specific adverse outcomes compared to controls. We will test whether these phenotypes replicate in the N3C data, and explore their translation into triage and treatment strategies.

Frequent freezing injury greatly influences winter wheat production; thus, effective prevention and a command of agricultural production are vital. The freezing injury monitoring method integrated with ‘3S’ (geographic information systems (GIS), global positioning system (GPS) and remote sensing (RS)) technology has an unparalleled advantage. Using HuanJing (HJ)-1A/1B satellite images of a winter wheat field in Shanxi Province, China plus a field survey, crop types and winter wheat planting area were identified through repeated visual interpretations of image information and spatial analyses conducted in GIS. Six vegetation indices were extracted from processed HJ-1A/1B satellite images to determine whether the winter wheat suffered from freezing injury and its degree of severity and recovery, using change vector analysis (CVA), the freeze injury representative vegetation index and the combination of the two methods, respectively. Accuracy of the freezing damage classification results was verified by determining the impact of freezing damage on yield and quantitative analysis. The CVA and the change of normalized difference vegetation index (ΔNDVI) monitoring results were different so a comprehensive analysis of the combination of CVA and ΔNDVI was performed. The area with serious freezing injury covered 0.9% of the total study area, followed by the area of no freezing injury (3.5%), moderate freezing injury (10.2%) and light freezing injury (85.4%). Of the moderate and serious freezing injury areas, 0.2% did not recover; 1.2% of the no freezing injury and light freezing injury areas showed optimal recovery, 15.6% of the light freezing injury and moderate freezing injury areas showed poor recovery, and the remaining areas exhibited general recovery.

The epidemic of tuberculosis has posed a serious burden in Qinghai province, it is necessary to clarify the epidemiological characteristics and spatial-temporal distribution of TB for future prevention and control measures. We used descriptive epidemiological methods and spatial statistical analysis including spatial correlation and spatial-temporal analysis in this study. Furthermore, we applied an exponential smoothing model for TB epidemiological trend forecasting. Of 43 859 TB cases, the sex ratio was 1.27:1 (M:F), and the average annual TB registered incidence was 70.00/100 000 of 2009–2019. More cases were reported in March and April, and the worst TB stricken regions were the prefectures of Golog and Yushu. High TB registered incidences were seen in males, farmers and herdsmen, Tibetans, or elderly people. 7132 cases were intractable, which were recurrent, drug resistant, or co-infected with other infections. Three likely cases clusters with significant high risk were found by spatial-temporal scan on data of 2009–2019. The exponential smoothing winters' additive model was selected as the best-fitting model to forecast monthly TB cases in the future. This research indicated that TB in Qinghai is still a serious threaten to the local residents' health. Multi-departmental collaboration and funds special for TB treatments and control are still needed, and the exponential smoothing model is promising which could be applied for forecasting of TB epidemic trend in this high-altitude province.

In order to intercept a highly manoeuvering target with an ideal impact angle in the three-dimensional space, this paper promises to probe into the problem of three-dimensional terminal guidance. With the goal of the highly target acceleration and short terminal guidance time, a guidance law, based on the advanced fast non-singular terminal sliding mode theory, is designed to quickly converge the line-of-sight (LOS) angle and the LOS angular rate within a finite time. In the design process, the target acceleration is regarded as an unknown boundary external disturbance of the guidance system, and the RBF neural network is used to estimate it. In order to improve the estimation accuracy of RBF neural network and accelerate its convergence, the parameters of RBF neural network are adjusted online in real time. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network, which improves the convergence speed of the guidance system. Theoretical analysis demonstrates that the state and the sliding manifold of the guidance system converge in finite time. According to Lyapunov theory, the stability of the system can be guaranteed by online adjusting the parameters of RBF neural network and adaptive parameters. The numerical simulation results verify the effectiveness and superiority of the proposed guidance law.

This work reports experimental observation and theoretical explanation of the dynamics and morphology of a droplet passing through a soap film. During the process, the film undergoes four sequential responses: (1) film deformation upon droplet impact; (2) drop–film detachment; (3) coalescence of the film shell with the drop; (4) peel-off of the film shell. Physical models and the corresponding analytical expressions are developed to reveal the underlying physics for the observed four responses. It is identified that the film is an elongated catenoid under continuous stretch by the droplet, and that they separate at the fixed height of 5.8 times of the droplet radius while the detach point is located at the centre of the height. After separation, the droplet is wrapped with a film shell, which is then punctured by the ring tip of the converging surface wave at the impacting Weber number range of [45, 225]. The film shell then coalesces with the droplet, falls off with a fixed velocity and is eventually ejected as a bubble leaving the droplet with a transplanted surface of the soap solution.

Masturbation is a common sexual practice in men, and saliva is often used as a lubricant during masturbation by men who have sex with men. However, the role of saliva use during masturbation in the transmission of chlamydia is still unclear. We developed population-level, susceptible-infected-susceptible compartmental models to explore the role of saliva use during masturbation on the transmission of chlamydia at multiple anatomical sites. In this study, we simulated both solo masturbation and mutual masturbation. Our baseline model did not include masturbation but included transmission routes (anal sex, oral-penile sex, rimming, kissing and sequential sexual practices) we have previously validated (model 1). We added masturbation to model 1 to develop the second model (model 2). We calibrated the model to five clinical datasets separately to assess the effects of masturbation on the prevalence of site-specific infection. The inclusion of masturbation (model 2) significantly worsened the ability of the models to replicate the prevalence of C. trachomatis. Using model 2 and the five data sets, we estimated that saliva use during masturbation was responsible for between 3.9% [95% confidence interval (CI) 2.0–6.8] and 6.2% (95% CI 3.8–10.5) of incident chlamydia cases at all sites. Our models suggest that saliva use during masturbation is unlikely to play a major role in chlamydia transmission between men, and even if it does have a role, about one in seven cases of urethral chlamydia might arise from masturbation.

Of 100 patients discharged from short-stay units (SSUs) with antibiotics, 47 had a skin and soft-tissue infection, 22 had pneumonia, and 21 had a urinary tract infection. Among all discharge antibiotic prescriptions, 78% involved antibiotic overuse, most commonly excess duration (54 of 100) and guideline discordant selection (44 of 100).

Manure is a primary source of methane (CH4) emissions into the atmosphere. A large proportion of CH4 from manure is emitted during storage, but this varies with storage methods. In this research, we tested whether covering a manure heap with plastic reduces CH4 emission during a short-term composting process. A static chamber method was used to detect the CH4 emission rate and the change of the physicochemical properties of cattle manure which was stored either uncovered (treatment UNCOVERED) or covered with plastic (treatment COVERED) for 30-day periods during the four seasons? The dry matter content of the COVERED treatment was significantly less than the UNCOVERED treatment (P < 0.01), and the C/N ratio of the COVERED treatment significantly greater than the UNCOVERED treatment (P > 0.05) under high temperature. In the UNCOVERED treatment, average daily methane (CH4) emissions were in the order summer > spring > autumn > winter. CH4 emissions were positively correlated with the temperature (R2 = 0.52, P < 0.01). Compared to the UNCOVERED treatment, the daily average CH4 emission rates from COVERED treatment manure were less in the first 19 days of spring, 13 days of summer, 10 days of autumn and 30 days of winter. In summary, covering the manure pile with plastic reduces the evaporation of water during storage; and in winter, long-term covering with plastic film reduces the CH4 emissions during the storage of manure.