Miracle-dz/UniFAR-FTUs huggingface dataset:
The Domain Adversarial and Spatial Fusion Semi-Supervised Seismic Impedance Inversion

The application of artificial intelligence in seismic impedance inversion makes the prediction of stratigraphic information more efficient. Semi-supervised framework for impedance inversion is the latest breakthrough method in this field. However, the 1-D semi-supervised methods now in use are unable to extract the spatiotemporal properties of the data solely through the network itself. Moreover, the initial model, a critical input for this method, is typically derived through extrapolation and interpolation of well log data. This can lead to significant errors, especially when the well data are sparse and the subsurface structures are complex. Well data only provide information for a limited section of the reservoir, thereby making it challenging to capture the overall behavior accurately. As a result, the creation of an accurate initial model is often fraught with errors. A more desirable approach is to use seismic attribute-guided methods, such as neural networks, which incorporate both seismic and well log data, leading to a more accurate low-frequency model with lateral variations. In this article, we develop a semi-supervised domain adversarial and spatial fusion (DASF) inversion framework. This method uses a 1-D convolutional neural network (CNN)-based global spatiotemporal analysis module and a 2-D CNN-based local spatiotemporal analysis module to complete the inversion and forward task simultaneously. Multiple spatiotemporal characteristics from two submodules can be successfully fused using an adaptive fusion approach. In this network, the step of extracting the initial model is incorporated into the learning process. Moreover, we adopt adversarial learning in the impedance domain to guide the training process, thereby reducing the network’s dependence on labels. The experiments on the synthetic and field dataset show that the proposed method can efficiently improve the prediction accuracy of the inversion results compared with conventional methods. Meanwhile, the local spatiotemporal analysis module can be used to create a more trustworthy initial model that incorporates the characteristic of seismic and well-logging data.
Pentacam Topography and Macular Optical Coherence Pentacam Topography and Macular Optical Coherence Tomography Findings In Eyes Presenting With Refractive And Tomography Findings In Eyes Presenting With Refractive And Axial Myopia Axial Myopia

Background : Myopia is circular refractive error in which parallel light rays enter eye and shift point of conjugate focus anteriorly in front of retina. High myopia is usually with ( > ¡ 6.00 SD) or axial length (AL) more than 26 mm. Aim and objectives : Goal of research is to identify the results in eyes presenting with refractive and axial myopia using macular optical coherence tomography and pentacam. Subjects and techniques : Research is prospective research that will be carried out on 60 eyes with high myopia more than or equal -6SD. Ages ranging from 20 to 70 years old. They will be divided into two groups A-refractive myopia B-axial myopia and meeting the inclusion criteria. Results : There was non-important variation among 2 tested groups concerning anterior segment parameters (CCT, ACD, and WTW). A negative relation between axial length and CMT. While, there was positive relationship among axial length, age and WTW. No relationship was shown among axial length and ACD. There was highly statistically signi ﬁ cant RPE thinning were found in axial myopia, While, CNV, RD and MH was with on statistical signi ﬁ cance. Conclusion : Assessing anterior and posterior segment is essential for patients with high myopia to detect various types of diseases or before planning for refractive surgeries, and for prescribing and exactly measuring power of contact lenses and IOLs.
Socioeconomic and Cultural Influences on the Prevalence of Obesity and Underweight

With great pleasure, I welcome you to the inaugural issue of new peer-reviewed, scientific publication—Antropology. How we can read on Home Page of the journal “Anthropology is the study of humankind and the behaviour of humans according to the diversity of societies from the origin to the present day. Anthropology explains both biological and sociocultural aspects of humans and related species like primates throughout the evolutionary period. ”
Frequency lock-in control and mitigation of vortex-induced vibrations of an airfoil using a conserved-mass nonlinear vibration absorber

We investigate the effectiveness of a vibration absorber on the vortex-induced vibration response of turbine blades during the frequency lock-in phase. A reduced order model is considered for a turbine blade and a von der Pol oscillator is used to model fluid blade interaction caused by the vertex shedding. A spring-mass-damper system is considered to model the vibration absorber. The advantage of the vibration absorber is demonstrated by simulating the nonlinear coupled four-degree-of-freedom aeroelastic system for the different sets of system parameters. We observe the dominance of a nonlinear vibration absorber over the linear vibration absorber only for the higher coupling parameter values. The analytical solution of the nonlinear coupled system is obtained through the method of multiple scales for the case of 1:1 internal resonance to identify the critical design parameters of the vibration absorber. We observe the high sensitivity of the system's frequency response towards the distance of the vibration absorber from the elastic axis, along with the absorber's damping, stiffness, and mass. Finally, we perform a parametric analysis on the lock-in the stability region to better understand the effect of the vibration absorber on the instability region.
Impact of introduction of rapid diagnostic tests for malaria on antibiotic prescribing analysis of observational and randomised studies in public and private healthcare

Objectives To examine the impact of use of rapid diagnostic tests for malaria on prescribing of antimicrobials, specifically antibiotics, for acute febrile illness in Africa and Asia. Design Analysisof nine preselected linked and codesigned observational and randomised studies (eight cluster or individually randomised trials and one observational study). Setting
Effects of nitrogen levels and harvest interval on the growth and yield of Moringa (Moringa Oleifera Lam) in Sudan Savanna of Nigeria

Field experiment was conducted under irrigation at Bayero University Kano, during 2011/2012 dry season to investigate the effects of different nitrogen levels and harvest interval on growth and leaf yield of Moringa ( Moringa oleifera (Lam )). The treatments consisted of four levels of nitrogen (0, 50, 100 and 150kg N ha -1 ) and three times of harvest interval (2, 3, and 4 weeks). These were arranged in a split plot design with the nitrogen levels allocated to the main plots while the harvest interval allocated to the sub plots and replicated four times. The data collected were subjected to analysis of variance (ANOVA) using the general linear model of GenStat and significant different means were separated using DMRT. The result shows that applications of nitrogen significantly increased plant height, number of leaflets per plant, plant stem diameter, number of branches per plant, fresh and dry weights per plant. Generally, 150kg N ha -1 level gave highest values for all the growth and yield characters assessed. The highest fresh and dry total leaf yields were also obtained with 150kg N ha -1 level. Increase in harvest interval significantly increased fresh and dry leaf yields of Moringa with the highest yields obtained from 4 weeks harvest interval. Nitrogen and harvest interval interaction was found to be significant on fresh and dry leaf yields of Moringa , which indicated that high yields were supported by 150kg N ha -1 at 4 weeks harvest interval. Keywords : Moringa , harvest interval, Nitrogen level, yield
A Panel Data Analysis of Albania’s Trade: The Gravity Model Approach

International trade allows countries to expand markets for goods and services that otherwise may not have been available. These trade benefits have encouraged countries to strengthen trade ties and seek new trade opportunities, Adam Hayes (2022). This paper aims to investigate the role of distance and economic mass in gravity regressions. It also estimates a non-linear gravity model for 24 main European trade partners with Albania from 2008 to 2020. This paper uses a data set of 312 observations for each of the three variables (a total of 936), organized in panel data obtained from the World Bank during the mentioned period. Three research questions are designed to achieve the goal related to economic mass and distance’s role in international trade, estimated elasticity coefficients, and the methods to evaluate the gravity model. The main findings explain that the Gravity Model successfully explains Albania’s bilateral trade, and the estimated elasticity coefficients can explain the extent of the trade response to the change of the variable in percentage. This information may be helpful for policymakers to improve the trade balance and to orient the economy toward sustainable development.
Progress in the Application of Artificial Intelligence in Ultrasound Diagnosis of Breast Cancer

The mammary gland is an important human organ that secretes milk and feeds offspring, while breast tumors are benign or malignant tumors that occur in the breast tissue. There are many causes of breast cancer, and the incidence continues to rise, which is an important killer that threatens women's health. In recent years, a large number of researchers have been interested in the study of AI diagnosis of breast cancer. Artificial intelligence uses a specific algorithm to intelligently process ultrasound images, and develops a high-precision and high-efficiency breast cancer recognition model through training and optimization of the algorithm. At present, the application of computer-aided detection methods in breast cancer ultrasound has been gradually promoted, and the combined application of artificial intelligence has played an advantageous role in the field of breast disease ultrasound diagnosis, such as shortening the examination time, effectively improving the detection rate and diagnostic accuracy rate. The main reasons are: the accuracy of traditional AI diagnosis model of breast cancer based on machine learning is not high; The aim of this paper is to improve the accuracy of early diagnosis of breast diseases effectively and reduce the misdiagnosis rate caused by overwork of doctors on the basis of clear medical images and computer-aided diagnosis technology.
Effect of Traditional Water Allocation Practices on the Environmental Flows In Ntcheu-Malawi: case study of Rivirivi River

The headwater catchments of the Rivirivi River basin play a vital role in meeting downstream water resources requirements. In recent years, the Rivirivi River has experienced significant changes in its hydrological regime, including an increased number of zero-flow days. These changes have serious implications on water security and basin management. This study was aimed at investigating the effect of traditional water allocation practices in the catchment on environmental flows. Water quantity indicators were assessed through flow duration analysis of the river flow regime behaviour before and after the introduction of the traditional water allocation practices. Further, desktop reserve model was applied to determine various categories of maintenance of high and low flows. Anthropogenic land use induced change patterns and their potential effect on water resources were investigated by time series analysis satellite imagery. Standard water quality assessment techniques were applied to assess spatial variation in water quality. The results indicate that there was a considerable difference in average annual stream flow between two identified main periods (between 1963 to 1983 and 1984 to 2004) and zero flows increased from 5% to 12%. The high flow index (Q5/Q50) increased by 16% between 1963 to 1983 and 1984 to 2004 whereas there is a dramatic reduction in the low flow index (Q95/Q50), with up to 100% reduction. Median flows (Q50) reduced by 8% in the same period. Further, the ecosystems need approximately the range of 35â€“40% of the MAR to be maintained at class A (Class A is streamflows with negligible modification from natural conditions and have negligible risk to sensitive species) and the range of 9â€“13% of MAR for class D (Class D is streamflow with high degree of modification from natural condition and intolerant biota unlikely to be present). In addition, the area experienced a 65% reduction in forest cover from 1992 to 2008 which resulted in increased high flow index by 16%. Furthermore, there was an overall significant spatial variation of chemical and physical water quality parameters in the catchment except for nitrates. However, the variations are within the Malawian standards of surface water quality set by MoIWD. The results suggest that traditional water allocation practices have negatively affected low flow environmental flows requirements by increasing zero flow days in Rivirivi River catchment. ,WATERnet
Inﬂuence of Sunn Hemp Biomass Incorporation on Organic Strawberry Production

: Sunn hemp ( Crotalaria juncea L.), a warm season leguminous cover crop, is commonly used in rotation with organic strawberry production in Florida’s subtropical environment. This study was conducted to explore the impacts of sunn hemp on growth and yield performance of the subsequent organic strawberry crop in sandy soils, taking into consideration the nutrient contribution from soil incorporation of sunn hemp biomass. Sunn hemp was seeded during the summer off-season and terminated before ﬂowering, three weeks prior to the fall planting of two strawberry cultivars (‘Strawberry Festival’ and ‘Camino Real’). With sunn hemp residues incorporated into the soil, two application rates of nitrogen (N) through pre-plant organic fertilization for the strawberry season were used, including N at a rate of 84 kg/ha, without consideration of the N credit from sunn hemp, and N at a rate of 19.8 kg/ha, with consideration of the estimated N credit from sunn hemp. A summer fallow without cover crop and with a pre-plant organic fertilizer application at the N rate of 84 kg/ha was included as the control. Overall, the sunn hemp incorporation at three weeks after termination did not beneﬁt the strawberry plant growth or fruit yield in this study, with rather low levels of soilborne pathogen and nematode infestations. Both sunn hemp treatments exhibited a signiﬁcantly lower level of total soil N compared to the summer fallow plots at the end of the strawberry season. The reduction in the pre-plant N fertilization resulted in lower above-ground plant dry weight and accumulation of N, phosphorus (P), and potassium (K) at the end of the strawberry season, along with fewer leaves and smaller crowns of the strawberry plants during the early season. Both sunn hemp treatments decreased early fruit yields, while the sunn hemp treatment with the reduced N fertilization also led to a signiﬁcant reduction in the total fruit number and weight, although no signiﬁcant differences in the whole-season marketable fruit yield were observed among the nutrient management treatments. Overall, ‘Strawberry Festival’ yielded higher than ‘Camino Real’, but the effects of nutrient management did not vary with the strawberry cultivars. Further studies are needed to enhance organic strawberry nutrient management involving rotational cover crops.
The maximum sum of the sizes of cross t -intersecting separated families

: For a set X and an integer r ≥ 0, let (cid:16) X ≤ r (cid:17) denote the family of subsets of X that have at most r elements. Two families A ⊂ (cid:16) X ≤ r (cid:17) and B ⊂ (cid:16) X ≤ s (cid:17) are cross t -intersecting if | A ∩ B | ≥ t for all A ∈ A , B ∈ B . In this paper, we considered the measures of cross t -intersecting families A ⊂ (cid:16) X ≤ r (cid:17) , B ⊂ (cid:16) X ≤ s (cid:17) , then we used this result to obtain the maximum sum of sizes of cross t -intersecting separated families.
Increased flexibility in base flow modelling using a power law transmissivity profile

The hydrological catchment model known as TOPMODEL, in its original and most widely‐used form, assumed that subsurface transmissivity decreases exponentially as subsurface water storage decreases. It has been shown that this leads to recession curves of discharge Q that take the form − dQ/dt = aQb, where a is a constant and b = 2. In order to reproduce a wider range of recession, or base flow, behaviour, a power function for transmissivity was subsequently incorporated into TOPMODEL as an alternative to the exponential function. This was claimed to extend the realistic values of b to range from 1 to 2, inclusive. We show here that the power transmissivity function can also generate values of b > 2 without making unrealistic assumptions (beyond those arguably made in the original TOPMODEL), thus generating recession curves consistent with catchments showing prolonged base flow. Furthermore, the power transmissivity function can generate recession curves that steepen with time (b < 1). Copyright © 2007 John Wiley & Sons, Ltd.
Predicting future hospital antimicrobial resistance prevalence using machine learning

Abstract Objectives Predicting antimicrobial resistance (AMR), a top global health threat, nationwide at a hospital level could help target interventions. Using machine learning, we exploit historical AMR and antimicrobial usage to predict future AMR. Methods Antimicrobial use and AMR prevalence in bloodstream infections in hospitals in England were obtained per hospital group (Trust) and financial year (FY, April-March) for 22 pathogen-antibiotic combinations (FY2016-2017-FY2021-2022). XGBoost model predictions were compared in a to previous value taken forwards, difference between the previous two years taken forwards and linear trend forecasting (LTF). XGBoost feature importances were to aid interpretability. Results Relatively limited year-to-year variability in AMR prevalence within Trust-pathogen-antibiotic combinations meant previous value taken forwards achieved a low mean absolute error (MAE). XGBoost models performed similarly, while difference between the previous two years taken forwards and LTF were consistently worse. XGBoost considerably outperformed all other methods in Trusts with a larger change in AMR prevalence from FY2020-2021 (last training year) to FY2021-2022 (held-out test set). Feature importance values indicated that complex relationships were exploited for predictions. Conclusion Year-to-year resistance has generally changed little within Trust-pathogen-antibiotic combinations. In those with larger changes, XGBoost models could improve predictions, enabling informed decisions, efficient resource allocation, and targeted interventions.
Systematic Literature Review of Risk Factors for Poor Outcomes Among Adults With Respiratory Syncytial Virus Infection in High-Income Countries

Abstract Identification of risk factors for severe respiratory syncytial virus (RSV) disease in adults could facilitate their appropriate vaccine recommendations. We conducted a systematic literature review (last 10 years in PubMed/Embase) to identify quantitative estimates of risk factors for severe RSV infection outcomes in high-income countries. Severe outcomes from RSV infection included hospitalization, excess mortality, lower respiratory tract infection, or a composite measure: severe RSV, which included these outcomes and others, such as mechanical ventilation and extended hospital stay. Among 1494 articles screened, 26 met eligibility criteria. We found strong evidence that the following increased the risk of severe outcomes: age, preexisting comorbid conditions (eg, cardiac, pulmonary, and immunocompromising diseases, as well as diabetes and kidney disease), and living conditions (socioeconomic status and nursing home residence). The frequency of severe outcomes among younger adults with comorbidities was generally similar to that experienced by older adults, suggesting that immunosenescence and chronic conditions are both contributing factors for elevated risk. Trial registration PROSPERO (CRD42022315239).
Activity-dependent ectopic action potentials in regular-spiking neurons of the neocortex

Introduction Action potentials usually travel orthodromically along a neuron’s axon, from the axon initial segment (AIS) toward the presynaptic terminals. Under some circumstances action potentials also travel in the opposite direction, antidromically, after being initiated at a distal location. Given their initiation at an atypical site, we refer to these events as “ectopic action potentials. ” Ectopic action potentials (EAPs) were initially observed in pathological conditions including seizures and nerve injury. Several studies have described regular-spiking (RS) pyramidal neurons firing EAPs in seizure models. Under nonpathological conditions, EAPs were reported in a few populations of neurons, and our group has found that EAPs can be induced in a large proportion of parvalbumin-expressing interneurons in the neocortex. Nevertheless, to our knowledge there have been no prior reports of ectopic firing in the largest population of neurons in the neocortex, pyramidal neurons, under nonpathological conditions. Methods We performed in vitro recordings utilizing the whole-cell patch clamp technique. To elicit EAPs, we triggered orthodromic action potentialswith either long, progressively increasing current steps, or with trains of brief pulses at 30, 60, or 100 Hz delivered in 3 different ways, varying in stimulus and resting period duration. Results We found that a large proportion (72.7%) of neocortical RS cells from mice can fire EAPs after a specific stimulus in vitro, and that most RS cells (56.1%) are capable of firing EAPs across a broad range of stimulus conditions. Of the 37 RS neurons in which we were able to elicit EAPs, it took an average of 863.8 orthodromic action potentials delivered over the course of an average of ~81.4 s before the first EAP was seen. We observed that some cells responded to specific stimulus frequencies while less selective, suggesting frequency tuning in a subset of the cells. Discussion Our findings suggest that pyramidal cells can integrate information over long time-scales before briefly entering a mode of self-generated firing that originates in distal axons. The surprising ubiquity of EAP generation in RS cells raises interesting questions about the potential roles of ectopic spiking in information processing, cortical oscillations, and seizure susceptibility.