Miracle-dz/UniFAR-FTUs huggingface dataset:
An MM-GTD analysis of the radiation from slots in planar and cylindrical perfectly-conducting structures with a surface impedance patch

Abstract : The radiation from a slot in an electrically large, perfectly conducting cylinder partly covered with an impedance surface is treated by a combination of the geometrical theory of diffraction (GTD) and the method of moments (MM). The method is far more efficient than MM solutions of conventional integral equations because a perturbation type integral equation which requires the unknown to be evaluated only over the impedance patch is employed in the present analysis. Furthermore, the GTD method can be systematically incorporated into this perturbation integral equation not only to provide substantial simplifications in the solution, but also to directly treat convex cylinders of variable curvature. Numerical results are presented for the two-dimensional circular cylinder case for different size cylinders, different surface impedance values, and for different size surface impedance patches. The radiation from slots in an infinite, planar perfectly-conducting surface which is partly covered with an impedance surface is also analyzed via the MM-GTD solution of the same perturbation type integral equation as in the cylinder case. A comparison of the antenna pattern calculations for the planar and cylindrical configurations indicates the effects of surface curvature especially in the region of space in which the slot is directly visible. (Author)
Detecting and reducing heterogeneity of error in acoustic classification

Passive acoustic monitoring can be an effective method for monitoring species, allowing the assembly of large audio datasets, removing logistical constraints in data collection and reducing anthropogenic monitoring disturbances. However, the analysis of large acoustic datasets is challenging and fully automated machine learning processes are rarely developed or implemented in ecological field studies. One of the greatest uncertainties hindering the development of these methods is spatial generalisability—can an algorithm trained on data from one place be used elsewhere? We demonstrate that heterogeneity of error across space is a problem that could go undetected using common classification accuracy metrics. Second, we develop a method to assess the extent of heterogeneity of error in a random forest classification model for six Amazonian bird species. Finally, we propose two complementary ways to reduce heterogeneity of error, by (i) accounting for it in the thresholding process and (ii) using a secondary classifier that uses contextual data. We found that using a thresholding approach that accounted for heterogeneity of precision error reduced the coefficient of variation of the precision score from a mean of 0.61 ± 0.17 (SD) to 0.41 ± 0.25 in comparison to the initial classification with threshold selection based on F‐score. The use of a secondary, contextual classification with thresholding selection accounting for heterogeneity of precision reduced it further still, to 0.16 ± 0.13, and was significantly lower than the initial classification in all but one species. Mean average precision scores increased, from 0.66 ± 0.4 for the initial classification, to 0.95 ± 0.19, a significant improvement for all species. We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.
Adaptive PI and RBFNN PID Current Decoupling Controller for Permanent Magnet Synchronous Motor Drives Hardware-Validated Results

This study presents an adaptive proportional-integral (PI) and radial basis function neural network proportional-integral-derivative (PID) current control solution for permanent magnet synchronous motor (PMSM) drives. The proposed controller includes four controls: a decoupling term, a PI term, a supervision term, and a radial basis neural network-PID (RBFNN-PID) term. The first control term makes up the nonlinear factors, the second automatically adjusts the control gains, the third guarantees the system stability, and the fourth optimizes the PID parameters to achieve optimal system performance. Unlike off-line tuned PID controllers, the adaptive controller includes an adaptive tuning method for the on-line adjustment of control gain based on the gradient descent strategy. Therefore, it can be adjusted and handle the uncertainty of any system parameters. The program is not only simple and easy to be implemented but also ensures the accuracy and rapidity of the tracking speed. The control system has proven to be asymptotically stable. To verify the theory and application of the algorithm, a comparative experiment between the adaptive PI + RBFNN-PID controller and traditional PI + PID controller was conducted, demonstrating good robustness, which can effectively improve the PMSM. The results confirm that the proposed design achieves excellent control stability (i.e., quicker transient responding and smaller steady state error) in the presence of parametric uncertainty compared to conventional PID methods.
A Systematic Review to Compare Adverse Pregnancy Outcomes in Women with Pregestational Diabetes and Gestational Diabetes

Pregestational type 1 (T1DM) and type 2 (T2DM) diabetes mellitus and gestational diabetes mellitus (GDM) are associated with increased rates of adverse maternal and neonatal outcomes. Adverse outcomes are more common in women with pregestational diabetes compared to GDM; although, conflicting results have been reported. This systematic review aims to summarise and synthesise studies that have compared adverse pregnancy outcomes in pregnancies complicated by pregestational diabetes and GDM. Three databases, Pubmed, EBSCOhost and Scopus were searched to identify studies that compared adverse outcomes in pregnancies complicated by pregestational T1DM and T2DM, and GDM. A total of 20 studies met the inclusion criteria and are included in this systematic review. Thirteen pregnancy outcomes including caesarean section, preterm birth, congenital anomalies, pre-eclampsia, neonatal hypoglycaemia, macrosomia, neonatal intensive care unit admission, stillbirth, Apgar score, large for gestational age, induction of labour, respiratory distress syndrome and miscarriages were compared. Findings from this review confirm that pregestational diabetes is associated with more frequent pregnancy complications than GDM. Taken together, this review highlights the risks posed by all types of maternal diabetes and the need to improve care and educate women on the importance of maintaining optimal glycaemic control to mitigate these risks.
Effect of Anterior Chamber Depth on the Development of Post YAG LASER Capsulotomy Macular Edema

Background: The most common long-term phacoemulsification cataract surgery complication is the opacification of the posterior capsule (PCO). This condition can lead to decreased vision, an impaired ability to distinguish between light and dark and the development of monocular diplopia as the result of posterior capsule opacification. Aim of The Work: To evaluate correlation between anterior chamber depth using Anterior segment OCT and assess macular thickness after YAG-LASER capsulotomy using macular OCT. Patients and Methods: The study included twenty eyes of twenty patients who had uncomplicated phacoemulsification and developed posterior capsular opacification Group(1), and 20 eyes of 20 patients who had successful phacoemulsification without complications and without PCO Group (2) were the control. They were from the Sayed Galal Hospital Ophthalmology outpatient clinic from June to December 2021 at Al-Azhar University's Faculty of Medicine. Results: The current showed that best corrected visual acuity, spherical error, and spherical equivalent improved after YAG-Laser capsulotomy and vision markedly improved at the last follow-up period with statistically highly considerable variation between the two periods (p<0.001), while the axial length decreased during the follow-up period with statistically different value between the two periods (p<0.05). Conclusion: The blood-aqueous barrier is damaged by YAG-LASER capsulotomy, releasing VEGFs and other inflammatory mediators. The anterior chamber depth was altered by inflammatory macular edema from Nd:YAG laser capsulotomy. Prophylactic therapy may not be needed.
Extension and Evaluation of SSC for Removing Wideband RFI in SLC SAR Images

Synthetic aperture radar (SAR), as a wideband radar system, is easily contaminated by radio frequency interference (RFI), which affects the imaging quality of SAR. The subband spectral cancellation (SSC) method and its modifications utilize the SAR single-look complex (SLC) image to realize RFI extraction and mitigation by subtracting between sub-images, which are robust and efficient for engineering applications. In the past, the traditional SSC was often applied to narrowband interference (NBI) mitigation. However, when it was used for wideband interference (WBI) mitigation, it would cause the mitigated image to lose much of its useful information. In contrast, this paper proposes an improved SSC method based on successive cancellation and data accumulation (SSC-SCDA) for WBI mitigation. First, the fast Fourier transform (FFT) is used to characterize the SAR SLC data in the frequency domain, and the average range spectrum algorithm is used to detect whether there are interference components in the SAR SLC data. Then, according to the carrier frequency and bandwidth of the RFI in the frequency domain, the subbands are divided, and a cancellation strategy is formulated. Finally, based on the successive cancellation and data accumulation technology, WBIs can be removed by using only a small percentage of the clean subbands. Based on the simulated experiments, the interference mitigation performance of the proposed method is analyzed when the interference-to-signal bandwidth ratio (ISBR) varies from 20% to 80% under different signal-to-interference-to-noise ratios (SINR). The experimental results based on WBI-contaminated European Space Agency (ESA) Sentinel-1A SAR SLC data demonstrate the effectiveness of the proposed method in WBI mitigation.
Systematic Climate Model Biases in the Large‐Scale Patterns of Recent Sea‐Surface Temperature and Sea‐Level Pressure Change

Observed surface temperature trends over recent decades are characterized by (a) intensified warming in the Indo‐Pacific Warm Pool and slight cooling in the eastern equatorial Pacific, consistent with Walker circulation strengthening, and (b) Southern Ocean cooling. In contrast, state‐of‐the‐art coupled climate models generally project enhanced warming in the eastern equatorial Pacific, Walker circulation weakening, and Southern Ocean warming. Here we investigate the ability of 16 climate model large ensembles to reproduce observed sea‐surface temperature and sea‐level pressure trends over 1979–2020 through a combination of externally forced climate change and internal variability. We find large‐scale differences between observed and modeled trends that are very unlikely (<5% probability) to occur due to internal variability as represented in models. Disparate trends in the ratio of Indo‐Pacific Warm Pool to tropical‐mean warming, which shows little multi‐decadal variability in models, hint that model biases in the response to historical forcing constitute part of the discrepancy.
EFFECT OF PRECEDING CROPS, ORGANIC AND MINERAL NITROGEN AND PLANT DENSITY ON PRODUCTIVITY OF MAIZE PLANT

Two field experiments were conducted at El-Serw Agricultural Research Station, Agric. Research Center (ARC) during the two summer seasons of 1999 and 2000. The study aimed to find out the effect of different winter preceding crops, i.e. faba bean, wheat and sugar beet and different sources of nitrogen fertilization at rate of 120 kg N/fad (100 % mineral N, 100 % organic N, 25 % mineral N + 75 % organic N, 75 % mineral N + 25 % organic N) and three plant densities (20000, 24000 and 30000 plants/fad) as well as their interactions on growth yield and yield components of maize cv. TWC 321. A split-split plot design with three replications was used. The main findings could be summarized as follows: of nitrogen in the first season. 5- Maximum maize grain yield ard/fad was produced from planting faba bean as preceding crop interacted with 120 kg N/fad as (75 % mineral nitrogen + 25 % organic nitrogen) and with density of 30000 plants/fad. This is the recommendation for raising maize productivity under the conditions of El-Serw district.
Acidification, deoxygenation, and nutrient and biomass declines in a warming Mediterranean Sea

Abstract. The projected warming, nutrient decline, changes in net primary production, deoxygenation and acidification of the global ocean will affect marine ecosystems during the 21st century. Here, the climate change-related impacts on the marine ecosystems of the Mediterranean Sea in the middle and at the end of the 21st century are assessed using high-resolution projections of the physical and biogeochemical state of the basin under Representative Concentration Pathways (RCPs) 4.5 and 8.5. In both scenarios, the analysis shows changes in the dissolved nutrient contents of the euphotic and intermediate layers of the basin, net primary production, phytoplankton respiration and carbon stock (including phytoplankton, zooplankton, bacterial biomass and particulate organic matter). The projections also show uniform surface and subsurface reductions in the oxygen concentration driven by the warming of the water column and by the increase in ecosystem respiration as well as an acidification signal in the upper water column linked to the increase in the dissolved inorganic carbon content of the water column due to CO2 absorption from the atmosphere and the increase in respiration. The projected changes are stronger in the RCP8.5 (worst-case) scenario and, in particular, in the eastern Mediterranean due to the limited influence of the exchanges in the Strait of Gibraltar in that part of the basin. On the other hand, analysis of the projections under the RCP4.5 emission scenario shows a tendency to recover the values observed at the beginning of the 21st century for several biogeochemical variables in the second half of the period. This result supports the idea – possibly based on the existence in a system such as the Mediterranean Sea of a certain buffer capacity and renewal rate – that the implementation of policies for reducing CO2 emission could indeed be effective and could contribute to the foundation of ocean sustainability science and policies.
An Analytical Study of Creeping Flow of a Second-Order Fluid through a Small Diameter Leaky Tube with Linearly Diminishing Absorption

This study is focused on investigating the effects of linear absorption parameter on creeping flow of a second-order fluid through a narrow leaky tube. These flows are experienced in several biological and industrial procedures, for instance, in proximal convoluted tubule of a human kidney, in hemodialysis devices, in filtration processes of food industry, journal bearing, and slide bearing. Inertial effects are neglected due to creeping motion assumption and low Reynolds number. Langlois recursive approach method is used to linearize the governing compatibility equation and to obtain an approximate analytical solution by reverse solution method. Analytical expressions for various physically important quantities like velocity profile, bulk flow, mean pressure drop in longitudinal direction, wall shear stress, leakage flux, fractional absorption, and stream function are obtained in dimensionless form. The obtained solution shows great similarity with the already available work in the literature. Variation in flow variables with linear absorption parameter is analysed in detail. The special case of uniform absorption in creeping motion of second-order fluid is presented in a separate section. It is noticed that velocity field, in case of uniform absorption, is independent of non-Newtonian parameters. Therefore, it is asserted that any two dimensional axisymmetric Newtonian velocity fields is also a solution for second-order fluids with identical boundary conditions.
Projecting the impact of air pollution on child stunting in India—synergies and trade-offs between climate change mitigation, ambient air quality control, and clean cooking access

Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution, both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2 °C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), a multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2 °C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020–50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India.
Understanding Big Data-Business Alignment from a Dynamic Perspective

ABSTRACT With the ubiquitous adoption of big data, aligning big data with enterprises has become an increasingly critical issue for managers. To address this issue, we conducted a longitudinal case study to analyze big data-business alignment in manufacturing companies (Gree Electric in particular). We collected research data by visiting the company, interviewing corporate executives, and searching authoritative websites We then analyzed the alignment process through a four-step grounded process. Our findings indicate that the enterprise can develop dynamic capabilities through alignment actions that respond to big-data usage scenarios and thus realize the ultimate alignment between the business and big data. Our study conceptualizes this alignment process and provides meaningful implications for big data-business alignment. Based on the findings, we recommend that the enterprise’s alignment actions and dynamic capabilities should evolve in concert to achieve big data-business alignment, and thus offer practical guidance on the use of big data in manufacturing companies.
CIBAR: Stata module to plot bar graphs and confidence intervals over groups

cibar plots bars and confidence intervals of the mean of a variable over at least one group. cibar aims at drawing graphs that resemble graphs created by graph bar varname, over(varname) asyvar, adding confidence intervals to the bars. In order to do so, cibar uses Stata's twoway bar and twoway rcap. cibar shows graphically the differences in the mean of a variable depending on the categories of other variables.
Novel UHRF1-MYC Axis in Acute Lymphoblastic Leukemia

Simple Summary We provided evidence that ubiquitin-like, containing PHD and RING finger domain, 1 (UHRF1) is overexpressed in acute lymphocytic leukemia (ALL). We further showed that UHRF1 directly interacts and regulates c-Myc expression to enable ALL cell growth through the cMYC-CDK4/6 phosphoRb-signaling axis. Abstract Ubiquitin-like, containing PHD and RING finger domain, (UHRF) family members are overexpressed putative oncogenes in several cancer types. We evaluated the protein abundance of UHRF family members in acute leukemia. A marked overexpression of UHRF1 protein was observed in ALL compared with AML. An analysis of human leukemia transcriptomic datasets revealed concordant overexpression of UHRF1 in B-Cell and T-Cell ALL compared with CLL, AML, and CML. In-vitro studies demonstrated reduced cell viability with siRNA-mediated knockdown of UHRF1 in both B-ALL and T-ALL, associated with reduced c-Myc protein expression. Mechanistic studies indicated that UHRF1 directly interacts with c-Myc, enabling ALL expansion via the CDK4/6-phosphoRb axis. Our findings highlight a previously unknown role of UHRF1 in regulating c-Myc protein expression and implicate UHRF1 as a potential therapeutic target in ALL.
Facial Nerve Reconstructive Surgery in Otorhinolaryngology and its Enhancement by Platelet- and Extracellular Vesicle-Rich Plasma Therapy

The facial nerve and its reconstructive surgical procedures are complex and challenging. The main function of facial nerve is namely motor innervation of facial muscles and its dysfunction presents as facial paralysis. Depending on the extent of facial nerve injury (neurapraxia, axonotmesis, neurotmesis) and consequently a physiological phenomenon of Wallerian degeneration, mechanism, location of the injury, time course of the paralysis and medical condition we decide about the type of the reconstructive surgery. Generally, possible surgical interventions to improve facial nerve functioning are mainly nerve decompression, neurorrhaphy/end-to-end anastomosis, interposition (cable) grafts and nerve rerouting. Moreover, most commonly nerves undergoing facial reconstruction are great auricular and sural nerves. In addition, nerve rehabilitation can be improved by using platelet-rich plasma (PRP/PVRP), applied directly to nerve. There are many roles of PVRP, described in the literature such as neuroprotective, neurogenic, neuroinflammatory, angiogenic role and improving hemostasis. Also, its neoplastic and proliferative effects were not reported. Considering all these features implementing PVRP in the facial nerve regenerative treatment has strong potential in the future. Keywords: Facial nerve; Reeconstructive surgery; Platelet and extracellular vesicle rich plasma; Nerve regeneration