Miracle-dz/UniFAR-FTUs huggingface dataset:
Miniaturized reconfigurable dielectric resonator antenna array with reduced beam squinting

In this study, a compact reconfigurable dielectric resonator antenna (DRA) array is proposed to operate in the band IEEE 802.11 WLAN. The main goal of this design is to propose an array feeding topology to avoid radiated beam squinting due to frequency alteration and acquire some gain enhancement with miniaturized array size. For that, the parallel–series geometry is used to layout a microstrip feeder with four output ports on the front plane. Each output port coupled with a rectangular slot (RS) at the bottom plane, and a rectangular dielectric resonator (RDR) mounted above the RS. The frequency reconfigurability is attained by employing PIN diodes that are integrated with the four output ports to operate as switches. Moreover, an impedance equivalent circuit model of the proposed array is postulated for studying the resonance behavior to ensure the validity of the proposed design prior to simulation and fabrication. The prototype 64 × 18 mm2 achieves frequency agility in the range of 5.8 to 5.17 GHz. Also, the realized gain ranges from 12.2 to 10. 5 dBi. The array specifications make it a decent potential candidate to be used for WLAN wireless systems.
An Adaptive Sparse Constraint ISAR High Resolution Imaging Algorithm Based on Mixed Norm

Based on the sparsity of inverse synthetic aperture radar (ISAR) signal, in this paper, a novel high resolution imaging algorithm is proposed. In this method, an optimal ISAR signal model based on mixed norm is established by using compressed sensing theory. The high-resolution ISAR image with short coherent accumulation time is realized by solving the optimization model. The main advantages of the proposed approach are: The model makes use of the l 2,0 mixed norm to realize faster convergence and improve the computational speed of the model solution obviously. Moreover, according to the result sparsity of each iteration under arbitrary noise, the regularization coefficient in the model can be adjusted adaptively, which avoids the complex process of repeated attempts, otherwise, the optimal coefficient needs to be estimated and attempted by the statistical characteristics of the noise and signal. The effectiveness of the proposed method is verified by simulated and measured data.
An Acoustic Wave Equation for Tilted Transversely Isotropic Media

A finite-difference method for computing the first arrival traveltimes by solving the Eikonal equation in the celerity domain has been developed. This algorithm incorporates the head and diffraction wave. We also adapt a fast sweeping method, which is extremely simple to implement in any number of dimensions, to obtain accurate first arrival times in complex velocity models. The method, which is stable and computationally efficient, can handle instabilities due to caustics and provide head waves traveltimes. Numerical examples demonstrate that the celerity-domain Eikonal solver provides accurate first arrival traveltimes. This new method is three times accurate more than the 2nd-order fast marching method in a linear velocity model with the same spacing.
Do Manufacturing Plants Respond to Exogenous Changes in Electricity Prices? Evidence From Administrative Micro-Data

Climate policy often implies increasing energy prices. Due to incomplete regulation across the globe, concerns about competitiveness and employment eﬀects play an important role in the policy debate. Using micro-data on electricity network charges and the oﬃcial plant census data for Germany, we study the impact of rising electricity costs on plant performance in German Manufacturing. Electricity network charges are determined through regulation in Germany and therefore exogenous to each individual manufacturing plant, while making up a substantial share of ﬁnal electricity prices. We ﬁnd evidence of negative own-price elasticities for electricity both in the long- and in the short-run. A one cent increase in average network charges leads to a decrease in electricity procurement of roughly 3 %. We do not ﬁnd any signiﬁcant eﬀects on revenues, investments or capital stocks.
Effects of laparoscopic sleeve gastrectomy on serum lncRNA levels in obese patients

Obesity is a disease associated with excessive fat accumulation in the body, which body mass index (BMI) is ≥30 kg/m. Bariatric surgery technique is one of the most common treatment options for obesity with the advantage of faster weight loss in a short time. lncRNAs play a role in adipogenesis and metabolic diseases, including obesity, type 2 diabetes, cardiovascular disease (CVD), osteoarthritis, and hypertension, so they are significant targets for therapeutic options. In this study, we aimed to determine lncRNAs and specific parameters that show different expressions in the plasma of patients with obesity. We included fifteen patients with BMI ≥30 kg/m2 before and <30 kg/m2 after laparoscopic sleeve gastrectomy (LSG) in the study. Total RNAs, including lncRNAs and other non-coding RNAs, were isolated from plasma samples of patients, and eight lncRNAs (H19, Neat1, HOTAIR, ANRIL, MALAT1, ATB, SNGH5, UCA1) were quantified by real-time PCR. Gene Ontology, KEGG, and relation of obesity analysis were utilized. Unpaired Student's t-test Pearson correlation analysis was used for statistical analysis. We observed a statistically significant increase in the expression levels of all lncRNAs in the patients with the post-operative BMI change. We have added a new dimension to the biomarker studies related to obesity and the clinical follow-up of patients undergoing LSG surgery. Further studies are required for enlighting the molecular mechanisms.
Global perspectives on trends in health higher education

Today, changes in political and economic conditions, epidemiological and sociological developments, and the advancement of science and technology have necessitated the health and medical education systems to change. Therefore, we conducted a study entitled “Global perspectives on trends in higher education in healthcare,” to improve the quality of healthcare so that it can be used as a model for predicting future events related to medical education. This futures study applied the social, technological, economical, ecological, political, values (STEEPV) model to identify and analyze the trends that affect medical education at different levels. To collect and analyze the data, a scoping review of the articles published from the year 2000 was conducted on the World Health Organization (WHO), Web of Science, Scopus, PubMed/MEDLINE, EMBASE, Science Direct, Google Scholar, EBSCO, and Cochrane databases. The review process was performed in five stages: 1- Determining the research question, 2- Identifying relevant studies, 3- Selecting the studies, 4- Charting the data, and 5- Analyzing data. The preferred reporting item for systematic review and meta-analysis (PRISMA) statement was used in the selection and screening of articles. A total of 213 articles were included in the study for qualitative synthesis. A total of 154 trends were identified using the STEEPV model at seven levels of health behaviors and patients, diseases and health problems, healthcare system, medical education system, medical education institutions, medical curricula, and teaching and learning. Considering the results of this study, it is possible to formulate proper and efficient future scenarios for the higher health education system. Also, it will be helpful for medical education policymaking.
Stay-green trait ameliorates combined heat and drought stress in wheat

The present study was carried out during rabi 2017-18 at ICAR-Indian Agricultural Research Institute, New Delhi to investigate the effect of stay-green trait on grain yield in wheat under combined heat and drought stress. Two high stay green (GCP 6 and GCP 33) and two low stay green (GCP 23 and GCP 30) Recombinant Inbred Lines (RILs) of wheat along with their parents (HI1500/DBW43) were grown in field conditions under timely sown with irrigation (control) and without irrigation (drought stress), and late sown with irrigation (heat stress) and without irrigation (combined heat and drought stress). High stay-green RILs showed the reduced levels of abscisic acid and ethylene production during anthesis stage under heat, drought and combined stress conditions as compared to low stay green RILs. Furthermore, there was significantly better yield was observed in high stay-green RILs as compared to low stay-green RILs. Thus our study concludes that stay-green traits improve the yield in wheat under combined heat and drought stress condition by delaying the senescence through reduced levels of abscisic acid and ethylene.
EMS-CDNet: an efficient multi-scale-fusion change detection network for very high-resolution remote sensing images

ABSTRACT Remote sensing image change detection (RSICD) is an essential measure for monitoring the earth’s surface changes. In recent years, the explosive growth of very high-resolution (VHR) satellite sensors and the booming innovations in deep learning technology have significantly boosted RSICD development. However, most of the current RSICD models focus on locating accurate change areas while ignoring the efficiency of their method, which limits the practical application of RSICD models, especially for large-scale and emergency RSICD tasks. In this paper, we propose an Efficient Multi-scale-fusion Change Detection Network (EMS-CDNet) for bi-temporal RSICD tasks. Our EMS-CDNet pays more attention to the model’s inference speed and the accuracy-efficiency trade-off rather than only pursuing detection accuracy. We designed a multi-scale fusion module for EMS-CDNet, which adopts multi-scale and multi-branch operations to extract multi-scale features simultaneously and aggregate features at different feature levels. In addition to EMS-CDNet’s ability to achieve sufficient feature extraction, the multi-scale image input within the designed module alleviates the influence of image registration errors in practical applications, thereby strengthening EMS-CDNet’s value for practical RSICD tasks. We also integrated a novel partition unit in EMS-CDNet to lighten the model while maintaining the detection ability of small targets, thus shortening its processing time without a severe accuracy decrease. We conducted experiments on two state-of-the-art (SOTA) public RSICD datasets and our own collected dataset. The public datasets were utilized to comparatively measure the overall accuracy and efficiency measurement of EMS-CDNet, and the dataset of images we collected was used to observe EMS-CDNet’s performance under the influence of image registration errors. Our experimental results show that EMS-CDNet achieved a better accuracy-efficiency trade-off than the SOTA public datasets methods. For example, EMS-CDNet reduced the inference time by about 33% while maintaining identical detection accuracy to CLNet (the optimal method among the comparison methods). Furthermore, EMS-CDNet achieved higher accuracy on our collected dataset, with an F1 of 74% and mIoU of 0.806, demonstrating its robustness to image registration errors and showing its value for practical RSICD applications.
Distribution of spectral weight in a system with disordered stripes

The "band structure" of a disordered stripe array is computed and compared, at a qualitative level, to angle-resolved photoemission experiments on cuprate high-temperature superconductors. The low-energy states are found to be strongly localized transverse to the stripe direction, so the electron dynamics is strictly one dimensional (along the stripe). Despite this, aspects of the two dimensional band-structure Fermi surface are still vividly apparent.
Effect of intra-articular hyalase, Ketorolac, marcaine and triamcinolone, versus Ketorolac, marcaine and triamcinolone for reducing knee joint pain other than joint replacement

Introduction: Knee pain is one of the causes of physiological complications in patients with osteoarthritis of the knee. It is necessary to provide a solution to reduce pain in these patients. Our study aimed to compare the effect of intra-articular hyalase, ketorolac, marcaine, and triamcinolone versus ketorolac, marcaine, and triamcinolone for reducing knee joint pain after knee surgery. Methods: This clinical study was performed on 30 candidates for knee surgery other than knee replacement from 2019 to 2020. The patients were randomly divided into two groups: hyalase, ketorolac, marcaine, and triamcinolone (group 1) and ketorolac, marcaine, and triamcinolone (group 2). The patient's pain score was recorded by the Numeric Rating Scale (NRS) and range of motion (ROM) at the end of the first week, the end of the first month, and the end of the third month as well as the sixth month and the twelfth month after surgery. Results: The mean age of the patients was 42.3 years. On average, the group receiving hyalase (first group) received about 30% better scores and had less pain (P < 0.05). In the first week, first month, and third month, no significant difference was observed between the two groups. But the pain scores for the first and second groups were 3.1 and 4.5 during the sixth to twelfth months, respectively (P < 0.05). Moreover, the increase in ROM during the sixth to twelfth months was significantly higher in the group receiving hyalase (P < 0.05). Conclusion: Adding hyalase to ketorolac, marcaine, and triamcinolone could improve pain control in the short and long term and this could be capable of reducing the need for additional drugs.
Six Blind Men and One Elephant: Proposing an Integrative Framework to Advance Research and Practice in Justice Philanthropy

There are growing calls that philanthropic foundations across the globe can and should advance diversity, equity, inclusion, and justice. Initial evidence indicates that foundations have indeed responded as evidenced by pledges to change practice, increased funding for racial justice, and the emergence of new networks to support equity and justice. However, there is also great skepticism about whether the field of foundations are, in fact, able to make lasting changes given numerous critiques of philanthropy and its structural limitations. In this article, we summarize these critiques that suggest factors that make institutional philanthropy resistant to calls for equity and justice. We posit that a core obstacle is a lack of conceptual coherence within and across academic and practitioner literature about the meanings of terms and their implications for practice. Therefore, we propose a transdisciplinary conceptual framework of justice philanthropy that integrates the fragmented literature on justice-related aspects of philanthropy emerging from different disciplinary traditions such as ethics, political theory and political science, social movement theory, geography, public administration, and community development.
Optimized complex object classification model: reconstructing the ISAR image of a hypersonic vehicle covered with a plasma sheath using a U-WGAN-GP framework

ABSTRACT This study aims to apply generative adversarial networks (GANs) to the effective classification of high/low resolution (HR/LR) image pairs obtained via inverse synthetic aperture radar (ISAR) for hypersonic objects covered with a plasma sheath. We propose a classification training model based on a Wasserstein GAN with a gradient penalty (U-WGAN-GP) framework, wherein a U-Net with an excellent jump connection structure is used as a generator, and a VGG-Net with high robustness is used as a discriminator, to support the reliable classification of HR/LR ISAR image pairs for the enhancement of ISAR image resolution. The WGAN-GP provides a shortcut for the gradient propagation of network parameters during the training stage through the stable encoder and decoder structure of U-Net. It inherits the echo intensity variation and position distribution characteristics of the scattering points between hypersonic objects in LR images and effectively transplants them into the generated super-resolution ISAR images, and it establishes end-to-end mapping between the HR/LR ISAR images. Moreover, the VGG-Net ensures that the generated super-resolution images are stable, controllable, and undistorted. In addition, the WGAN-GP structure combines the content and adversarial losses, optimizes the generator loss function, and uses the GP method to provide a stable and continuous training process. Finally, a traditional VGG-16 network classifier is added at the end of the training model. The proposed model is applied to an HR/LR image pair dataset of hypersonic objects. Compared with existing methods, the proposed method improved the classification and recognition accuracy from 54.4% to 81.8%.
Time-dependent pointer states of the generalized spin-boson model and consequences regarding the decoherence of the central system

We consider a spin-boson Hamiltonian which is generalized such that the Hamiltonians for the system ($\hat{H}_{\cal S}$) and the interaction with the environment ($\hat{H}_{\rm int}$) do not commute with each other. Considering a single-mode quantized field in exact resonance with the tunneling matrix element of the system, we obtain the time-evolution operator for our model. Using our time-evolution operator we calculate the time-dependent pointer states of the system and the environment (which are characterized by their ability not to entangle with each other) for the case that the environment initially is prepared in the coherent state. We show that our solution for the pointer states of the system and the environment is valid over a length of time which is proportional to $\bar{n}$, the average number of bosons in the environment. We also obtain a closed form for the offdiagonal element of the reduced density matrix of the system and study the decoherence of the central system in our model. We show that for the case that the system initially is prepared in one of its pointer states, the offdiagonal element of the reduced density matrix of the system will be a \emph{sinusoidal function} with a slow decaying envelope which is characterized by a decay time proportional to $\bar{n}$; while it will experience a much faster decoherence, when the system initially is \emph{not} prepared in one of its initial pointer states.
How Do Non-UN Peacekeepers Affect Civilian Violence? An Instrument Investigation

ABSTRACT This research note extends the Bara and Hultman (2020) study on the effectiveness of non-UN peacekeeping missions in terms of curbing one-sided violence (OSV) against civilians. In particular, we employ two novel instruments to address the two-way causality between the number of non-UN peacekeepers and OSV measures. For each panel year, our instruments involve the interaction between the sum of various designated peacekeepers contributed and the inverse distance between the capitals of contributor and conflict countries. As required, the instrument satisfies the necessary inclusion and exclusion (exogeneity) requirements. The instrument-based results establish a robust reduction in government OSV stemming from the number of non-UN peacekeepers deployed. That reduction also holds for propensity-score matching and the inclusion of UN peacekeepers in the same regression. Non-UN peacekeepers did not have a robust influence on rebel OSV.
Planares: análise e sugestões de aperfeiçoamentos

Visando reduzir as enormes ineficiências dos padrões de produção e consumo expressos por meio dos resíduos gerados pela sociedade e os consequentes custos socioambientais e econômicos, uma gama crescente de políticas vem sendo criada e implementada em todo o mundo. Este trabalho traz evidências de que a política recém-lançada no Brasil (Planares) deu o tom nacionalmente, com conceitos parcialmente desatualizados e indicadores duvidosos e, portanto, já está madura para uma nova revisão. Tais revisões podem, contudo, ser feitas em nível municipal, como demonstrado no caso de São José dos Campos e sem custo adicional.
Formation Optimization, Characterization and Antioxidant Activity of Auricularia auricula-judae Polysaccharide Nanoparticles Obtained via Antisolvent Precipitation

Auricularia auricula-judae polysaccharide (AAP)-based nanoparticles (NPs) prepared via an anti-solvent precipitation approach were studied. Response surface methodology (RSM) design was carried out on the basis of single factor experiments, using average size and polydispersity index (PDI) as indicators. The optimal preparation conditions were determined to include an AAP concentration of 1 mg/mL, a pH of 8, and an anti-solvent/solvent volume ratio of 6. The average particle sizes of the AAP-NPs, PDI and electrical characteristic (ζ-potential) were found to be 150.27 ± 3.21 nm, 0.135 ± 0.012 and −31.10 ± 0.52 mV, respectively. Furthermore, Fourier transform infrared spectroscopy (FTIR) was used to determine the chemical structure of the AAP-NPs. It was observed that the intensity of AAP-NPs in the wide spectral band of 3000–3750 cm−1 was significantly stronger than that of the AAP, as was the characteristic peak of carboxyl anion, and the characteristic band moved to shorter wavelengths. Subsequent thermogravimetric analysis showed that the antisolvent precipitation method improved the thermal stability of the AAP, while scanning electron microscopy (SEM) and X-ray diffraction (XRD) showed that the morphology of AAP-NPs was uniform and well-distributed, and that their single crystal structures had remained unaffected during the process. Moreover, the DPPH and ABTS scavenging activities of AAP-NPs were increased, and the IC50 values were 0.544 ± 0.241 mg/mL and 0.755 ± 0.226 mg/mL, respectively.
Victimización (Bullying) según enfoque de género en adolescentes escolares de Huamanga y Sicuani

Introducción. La victimización escolar es un problema vigente en el Perú. El enfoque de género en el análisis de sus características permitirá adaptar estrategias de intervención diferenciadas. Objetivo. Determinar los factores de riesgo de victimización según enfoque de género en adolescentes escolares de las ciudades de Huamanga y Sicuani. Diseño. Estudio observacional transversal analítico. Participantes. 1160 alumnos de primero a quinto de secundaria de dos colegios (privado y público) en Huamanga y Sicuani. Intervención. Encuesta validada para identificar víctimas de bullying. Análisis. Descriptivo, chi-cuadrado, OR (IC95%) y análisis multivariado de regresión logística. Se utilizó SPSS v. 15. Principales medidas de resultados. Porcentaje y factores de riesgo de victimización escolar. Resultados. El 37,3% de estudiantes fueron victimizados. En varones, “ha presenciado algún acto violento” 1,72 (1,122 – 2,636); en mujeres “vivir con uno de los padres” 1,682 (1,072 – 2,641); en “Huamanga” 1,767 (1,119 – 2,790); en ambos sexos “tener algún defecto físico” y “padres reaccionan con violencia cuando se portan mal” fueron los factores de riesgo más importantes. Formas de victimización más reportadas en ambos sexos fueron “te pusieron apodos” y “has sido discriminado”. Predominó en varones, las formas directas como “te llamaron homosexual” y “has sido golpeado”; y en mujeres las indirectas. Conclusiones. La victimización escolar es problema importante. En mujeres estuvo asociada con características individuales y familiares; y en varones con la seguridad escolar. Las formas directas de victimización se relacionaron con varones.