Miracle-dz/UniFAR-FTUs huggingface dataset:
Bandwidth enhancement of a microstrip-line-fed printed wide-slot antenna

Printed wide-slot antennas fed by a microstrip line with a fork-like tuning stub for bandwidth enhancement are proposed and experimentally investigated. Both the impedance and radiation characteristics of this antenna are studied. Experimental results indicate that a 1:1.5 VSWR bandwidth of 1 GHz is achieved at operating frequencies around 2 GHz, which is nearly ten times that of a conventional microstrip-line-fed printed wide-slot antenna. It also achieved a 2-dB gain bandwidth of at least 0.5 GHz.
Current Views on Infective Endocarditis: Changing Epidemiology, Improving Diagnostic Tools and Centering the Patient for Up-to-Date Management

Infective endocarditis (IE) is a rare but potentially life-threatening disease, sometimes with longstanding sequels among surviving patients. The population at high risk of IE is represented by patients with underlying structural heart disease and/or intravascular prosthetic material. Taking into account the increasing number of intravascular and intracardiac procedures associated with device implantation, the number of patients at risk is growing too. If bacteremia develops, infected vegetation on the native/prosthetic valve or any intracardiac/intravascular device may occur as the final result of invading microorganisms/host immune system interaction. In the case of IE suspicion, all efforts must be focused on the diagnosis as IE can spread to almost any organ in the body. Unfortunately, the diagnosis of IE might be difficult and require a combination of clinical examination, microbiological assessment and echocardiographic evaluation. There is a need of novel microbiological and imaging techniques, especially in cases of blood culture-negative. In the last few years, the management of IE has changed. A multidisciplinary care team, including experts in infectious diseases, cardiology and cardiac surgery, namely, the Endocarditis Team, is highly recommended by the current guidelines.
Wavelet-MDL based detrending method for near infrared spectroscopy (NIRS)

Near infrared spectroscopy (NIRS) is a relatively new non-invasive brain imaging method to measure brain activities associated with regional changes of the oxy- and deoxy- hemoglobin concentration. Typically, functional MRI or PET data are analyzed using the general linear model (GLM), in which measurements are modeled as a linear combination of explanatory variables plus an error term. However, the GLM often fails in NIRS if there exists an unknown global trend due to breathing, cardiac, vaso- motion and other experimental errors. In order to overcome these problems, we propose a wavelet-MDL based detrending algorithm. Specifically, the wavelet transform is applied to NIRS measurements to decompose them into global trends, signals and uncorrelated noise components in distinct scales. In order to prevent the over-fitting the minimum length description (MDL) principle is applied. Experimental results demonstrate that the new detrending algorithm outperforms the conventional approaches.
Optimization of Radar Interferometer Angle Measurement Based on Cubic Spline Interpolation

Radars often need to be calibrated to improve the accuracy of goniometric measurements. When the calibration value is difficult to approximate to a certain value, the calibration method is particularly important. This paper first introduces the interferometer angle measurement principle of a continuous wave radar under development, and then proposes a calibration optimization method based on cubic spline interpolation for the problems caused by early segment calibration, and compares the effects through experiments.
Axillary Treatment Management in Breast Cancer during COVID-19 Pandemic (Association between ACOSOG Z0011 Criteria and OSNA Test)

The outbreak of the SARS-COVID-2 pandemic (COVID-19) had a significant effect on the organisation of healthcare systems. Surgical units saw a significant reduction in the volume of surgical procedures performed, with lengthening waiting lists as a consequence. We assessed the surgical activity in relation to breast cancer that took place at the University Hospital of Cagliari, Italy, from February 2018 to March 2022. Two phases were identified based on the epidemiological circumstances: Phase 1—February 2018 to February 2020; Phase 2—March 2020 to March 2022. The surgery performed in the two phases was then compared. All the patients in our sample underwent a breast surgical procedure involving a lymph node biopsy using OSNA associated with the ACOSOG Z0011 criteria. In the study period overall at our facility, there were 4214 procedures, 417 of which involved breast surgery. In Phase 2, 91 procedures were performed using the OSNA method and ACOSOG Z0011 criteria, enabling the intraoperative staging of axillary nodes. Axillary treatment in breast cancer using this approach resulted in a significant reduction in the number of reoperations for the radicalisation of metastatic sentinel lymph nodes.
An Initial Evaluation of Arm’s Scalable Matrix Extension

Expanding upon their Scalable Vector Extension (SVE), Arm have introduced the Scalable Matrix Extension (SME) to improve in-core performance for matrix operations such as matrix multiplication. With the lack of hardware and cycle-accurate simulations available which supports SME, it is unclear how effective this new instruction set extension will be, and for what type of applications it will provide the most benefit.By adapting The Simulation Engine (SimEng) from the University of Bristol’s High Performance Computing Group to support SME, we aim to compare the simulated performance of a Fujitsu A64FX core (with native SVE support) to a like-for-like hypothetical core with added SME support. By simulating a wide range of Streaming Vector Lengths for our hypothetical SME core model, we provide and discuss first-of-a-kind results for an SME implementation, before discussing future work that will be carried out to further evaluate the suitability of SME.
Mesane Kanserinde İntravezikal Bacille Calmette- Guerin (BCG) Uygulaması ve Hemşirenin Sorumlulukları

Mesane kanseri, yaygın olarak görülen ürogenital bir malignitedir. Tüm mesane kanserlerinin yaklaşık %80'ini, kasa invaziv olmayan mesane kanserleri oluşturmaktadır. Kasa invaziv olmayan mesane kanserinin tedavi yöntemlerinden birisi de intravezikal immünoterapidir. İntravezikal immünoterapi amacıyla Bacille Calmette- Guerin (BCG) kullanılmaktadır ve bu yöntem oldukça etkilidir. BCG, Mycobacterium bovis'in canlı, zayıflatılmış bir formudur. Gerekli koruyucu önlemler alınmadığında, hastalar ve sağlık çalışanları ilacın zararlı etkilerine maruz kalabilmektedirler. İntravezikal BCG uygulaması, hastalarda lokal ve sistemik yan etkiler oluşturabilmektedir. Bu nedenle, hastaların tedavileri ertelenebilmekte veya tamamen kesilebilmektedir. Ayrıca yan etkiler, hastaların yaşam kaliteleri olumsuz etkilemektedir. Tedavinin başarıya ulaşmasında ve yan etkilerinin kontrol altına alınmasında intravezikal BCG uygulama ilkelerine uyulması ve gerekli koruyucu önlemlerin alınması önemlidir. Bu derleme ile, intravezikal BCG uygulama ilkeleri, hastalarda gelişebilecek olası yan etkiler ve bunların önlenmesi, semptom kontrolünün sağlanması, BCG uygulamasının kontrendike olduğu durumlar, BCG uygulama öncesi, sırası ve sonrasında alınması gereken güvenlik önlemleri ve BCG uygulayan hemşirenin sorumlulukları konusunda bilgi vermek amaçlanmaktadır.
U.S. Landfalling and North Atlantic Hurricanes: Statistical Modeling of Their Frequencies and Ratios

AbstractTime series of U.S. landfalling and North Atlantic hurricane counts and their ratios over the period 1878–2008 are modeled using tropical Atlantic sea surface temperature (SST), tropical mean SST, the North Atlantic Oscillation (NAO), and the Southern Oscillation index (SOI). Two SST input datasets are employed to examine the uncertainties in the reconstructed SST data on the modeling results. Because of the likely undercount of recorded hurricanes in the earliest part of the record, both the uncorrected hurricane dataset (HURDAT) and a time series with a recently proposed undercount correction are considered.Modeling of the count data is performed using a conditional Poisson regression model, in which the rate of occurrence can depend linearly or nonlinearly on the climate indexes. Model selection is performed following a stepwise approach and using two penalty criteria. These results do not allow one to identify a single “best” model because of the different model configurations (different SST d.
Solitons as dissipative structures

I review here recent results regarding the excitation of nonlinear interfacial oscillations, and hence waves, at the surface of a liquid or at the interface separating two liquids when a thermal gradient is imposed or there is adsorption, and subsequent absorption in the bulk, of a (light) surfactant, hence creating tangential stresses due to the surface tension gradient (Marangoni effect). I also recall their solitonic features upon collisions and boundary reflections, etc., even though the proposed evolution equations are not hyperbolic but a parabolic–hyperbolic combination like a dissipation-modified Boussinesq–Korteweg–de Vries equation. Theory, numerics, and experiments support my claim that solitons can exist and survive in a dissipative medium provided, for example, past an instability threshold, there is an appropriate input–output energy balance. This is very much like (steady) dissipative structures and, indeed, (nonlinear) waves traveling with constant velocity in the moving frame are steady dissipative structures. © 2004 Wiley Periodicals, Inc. Int J Quantum Chem, 2004
A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G

In recent years, tremendous advances have been made in the design and applications of wireless networks and embedded sensors. The combination of sophisticated sensors with wireless communication has introduced new applications, which can simplify humans’ daily activities, increase independence, and improve quality of life. Although numerous positioning techniques and wireless technologies have been introduced over the last few decades, there is still a need for improvements, in terms of efficiency, accuracy, and performance for the various applications. Localization importance increased even more recently, due to the coronavirus pandemic, which made people spend more time indoors. Improvements can be achieved by integrating sensor fusion and combining various wireless technologies for taking advantage of their individual strengths. Integrated sensing is also envisaged in the coming technologies, such as 6G. The primary aim of this review article is to discuss and evaluate the different wireless positioning techniques and technologies available for both indoor and outdoor localization. This, in combination with the analysis of the various discussed methods, including active and passive positioning, SLAM, PDR, integrated sensing, and sensor fusion, will pave the way for designing the future wireless positioning systems.
An extension to the NK fitness landscape model to study pleiotropy, epistasis, and ruggedness independently

The NK model is designed to study evolutionary adaptation in rugged fitness landscapes. The factor $K$ determines the number of interacting genes, their degree of pleiotropy and epistasis, and consequently the ruggedness of the fitness landscape. However, in natural organisms, the degree of epistatic interactions and the number of functions a gene can have are to a certain degree determining the ruggedness of the landscape. Still, pleiotropy and epistasis can evolve independently from each other, and are to some degree independent of the ruggedness of the landscape. Here, we propose an extension to the standard NK model to investigate these factors independently of each other. Over the course of evolution the computational model organisms can now change how their genes interact and how they control phenotypic traits. Further, the degree of epistasis and pleiotropy is affected by the ruggedness of the landscape and becomes reduced with increasing ruggedness. While this proves that the extension of the model performs as expected, the adaptations are minor, presumably because only relatively short periods of adaptations with few mutations can be studied.
Bifidobacterium: Host–Microbiome Interaction and Mechanism of Action in Preventing Common Gut-Microbiota-Associated Complications in Preterm Infants: A Narrative Review

The development and health of infants are intertwined with the protective and regulatory functions of different microorganisms in the gut known as the gut microbiota. Preterm infants born with an imbalanced gut microbiota are at substantial risk of several diseases including inflammatory intestinal diseases, necrotizing enterocolitis, late-onset sepsis, neurodevelopmental disorders, and allergies which can potentially persist throughout adulthood. In this review, we have evaluated the role of Bifidobacterium as commonly used probiotics in the development of gut microbiota and prevention of common diseases in preterm infants which is not fully understood yet. The application of Bifidobacterium as a therapeutical approach in the re-programming of the gut microbiota in preterm infants, the mechanisms of host-microbiome interaction, and the mechanism of action of this bacterium have also been investigated, aiming to provide new insights and opportunities in microbiome-targeted interventions in personalized medicine.
A Bilevel Graph Reinforcement Learning Method for Electric Vehicle Fleet Charging Guidance

This letter proposes a bilevel graph reinforcement learning method for electric vehicle (EV) fleet charging guidance, achieving collaborative optimization of the transportation-electrification coupled system. A dual-agent architecture is first constructed, where the upper-level is used for charging and the lower-level is used for routing. The EV traveling and charging behavior is characterized as a graph-structured interaction process. A graph attention network (GAT) is leveraged to extract the topology correlation and feature information. Then the extracted topology embedded with knowledge, as intermediate latent environment states, is fed into the underlying network of deep reinforcement learning (DRL). A DRL-based sequential scheduling pattern is developed to realize the guidance of multiple EVs. Extensive experimental results verify the superiority and adaptability of our proposed methodology.
Isolation and Characterization of Cellulose Microfibers from Colombian Cocoa Pod Husk via Chemical Treatment with Pressure Effects

One of the current challenges is to add value to agro-industrial wastes, and the cocoa industry generates about 10 tons of cocoa pod husks in Colombia for each ton of cocoa beans, which are incinerated and cause environmental damage. This study characterized the Colombian cocoa pod husk (CPH) and to isolate and characterize cellulose microfibers (tCPH) extracted via chemical treatment and pressure. Chemical and physical analyses of CPH were performed, and a pretreatment method for CPH fibers was developed, which is followed by a hydrolysis method involving high pressure in an autoclave machine with an alkaline medium (6% NaOH), and finally, bleaching of the fiber to obtain tCPH. The tCPH cellulose microfibers were also chemically and physically analyzed and characterized by infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermo-gravimetric analysis (TGA). Chemical and physical characterization showed a decrease in lignin content in tCPH. FTIR analysis showed the absence of some peaks in tCPH with respect to the CPH spectrum; XRD results showed an increase in crystallinity for tCPH compared to CPH, due to a higher presence of crystalline cellulose in tCPH. SEM images included a control fiber treated without high pressure (tCPHnpe), and agglomerated fibers were observed, whereas cellulose microfibers with a mean diameter of 10 ± 2.742 μm were observed in tCPH. Finally, with TGA and DTGA it was confirmed that in tCPH, the hemicellulose and lignin were removed more successfully than in the control fiber (tCPHnpe), showing that the treatment with pressure was effective at isolating the cellulose microfibers from cocoa pod husk.
Computer identification of musical instruments

The objective is to identify musical instruments using a computer. The characteristics of a musical instrument can be determined by the frequency spectrum of a specific note. The spectrum will vary for different instruments. This variation identifies the instrument. The waveforms of musical instruments (simulated by an electronic keyboard) are stored in the computer. Experimental data were collected for clarinet, trumpet, flute, accordion, violin, and piano. A computer program is developed to characterize the various spectra. The frequency of maximum power is determined first. Then the ratios of the power levels corresponding to the first five harmonics are calculated. For each instrument, the above ratios are determined from several trials. It is found that a characteristic feature of a musical instrument corresponds to specific values of these ratios. A computer program compares the ratios obtained from playing an instrument in real time with the stored ratios of various instruments to identify and disp.
Nano-Sized Fucoidan Interpolyelectrolyte Complexes: Recent Advances in Design and Prospects for Biomedical Applications

The marine polysaccharide fucoidan (FUC) is a promising polymer for pharmaceutical research and development of novel drug delivery systems with modified release and targeted delivery. The presence of a sulfate group in the polysaccharide makes FUC an excellent candidate for the formation of interpolyelectrolyte complexes (PECs) with various polycations. However, due to the structural diversity of FUC, the design of FUC-based nanoformulations is challenging. This review describes the main strategies for the use of FUC-based PECs to develop drug delivery systems with improved biopharmaceutical properties, including nanocarriers in the form of FUC–chitosan PECs for pH-sensitive oral delivery, targeted delivery systems, and polymeric nanoparticles for improved hydrophobic drug delivery (e.g., FUC-zein PECs, core-shell structures obtained by the layer-by-layer self-assembly method, and self-assembled hydrophobically modified FUC particles). The importance of a complex study of the FUC structure, and the formation process of PECs based on it for obtaining reproducible polymeric nanoformulations with the desired properties, is also discussed.
“Pulsed Hypoxia” Gradually Reprograms Breast Cancer Fibroblasts into Pro-Tumorigenic Cells via Mesenchymal–Epithelial Transition

Hypoxia arises in most growing solid tumors and can lead to pleotropic effects that potentially increase tumor aggressiveness and resistance to therapy through regulation of the expression of genes associated with the epithelial–mesenchymal transition (EMT) and mesenchymal–epithelial transition (MET). The main goal of the current work was to obtain and investigate the intermediate phenotype of tumor cells undergoing the hypoxia-dependent transition from fibroblast to epithelial morphology. Primary breast cancer fibroblasts BrC4f, being cancer-associated fibroblasts, were subjected to one or two rounds of “pulsed hypoxia” (PH). PH induced transformation of fibroblast-shaped cells to semi-epithelial cells. Western blot analysis, fluorescent microscopy and flow cytometry of transformed cells demonstrated the decrease in the mesenchymal markers vimentin and N-cad and an increase in the epithelial marker E-cad. These cells kept mesenchymal markers αSMA and S100A4 and high ALDH activity. Real-time PCR data of the cells after one (BrC4f_Hyp1) and two (BrC4f_Hyp2) rounds of PH showed consistent up-regulation of TWIST1 gene as an early response and ZEB1/2 and SLUG transcriptional activity as a subsequent response. Reversion of BrC4f_Hyp2 cells to normoxia conditions converted them to epithelial-like cells (BrC4e) with decreased expression of EMT genes and up-regulation of MET-related OVOL2 and c-MYC genes. Transplantation of BrC4f and BrC4f_Hyp2 cells into SCID mice showed the acceleration of tumor growth up to 61.6% for BrC4f_Hyp2 cells. To summarize, rounds of PH imitate the MET process of tumorigenesis in which cancer-associated fibroblasts pass through intermediate stages and become more aggressive epithelial-like tumor cells.
Comparing the efficacy and complications of Endoscopic Biliary Drainage (EBD) and Percutaneous Transhepatic Biliary Drainage (PTBD) in patients with perihilar cholangiocarcinoma

Introduction and Objective: Hilar cholangiocarcinoma (HCCA) is a rare malignancy in patients with biliary disease. If jaundice and obstruction before surgery are left untreated, then they can cause side effects such as cholangitis, delayed tumor treatment, decreased quality of life, and increased mortality. Surgery is the main treatment for HCCA. Therefore, this study was performed to compare the efficacy and complications of percutaneous transhepatic biliary drainage (PTBD) and endoscopic biliary drainage (EBD). Methods: This cohort study was conducted on 20 patients with biliary obstruction who had been selected by simple random sampling and divided into two groups of EBD and PTBD. Three weeks after surgery, patients were compared in terms of bilirubin levels and postoperative complications. Data were analyzed by descriptive statistics (table, mean, and standard deviation) and inferential statistics (independent t-test, Chi-square test, and Fisher's test). Results: Independent t-test did not show a significant difference between the two groups in terms of bilirubin level (P = 0.77). However, despite a decrease in bilirubin level in both groups, independent t-test showed that this difference was not significant (P = 0.08). Fisher's exact test showed a significant difference between the two groups in terms of postoperative complications (P = 0.02). Conclusion: Using both drainage methods before surgery reduced bilirubin levels in patients, but EBD method had fewer side effects than PTBD method. The EBD method was performed under the direct supervision of a gastroenterologist. In performing this procedure, specialist physicians should have more supervision.
Modern Diets and the Health of Our Planet: An Investigation into the Environmental Impacts of Food Choices

Popular modern diets are often seen as a panacea for improving health and promoting weight reduction. While there is a large body of literature reporting the health benefits of popular diets, few studies have described their planetary benefits. Our investigation aims to evaluate the simultaneous impacts of six popular diets within the United States on both human and planetary health. Using carbon footprint databases and representative meal plans, the environmental and health-related impacts of the Standard American, Mediterranean, vegan, paleo, keto, and climatarian diets are compared using the currently available literature. Results indicate that diets that exhibit lower carbon footprints also have positive effects on human health. The diets found to have the lowest environmental impacts were the vegan, climatarian, and Mediterranean diets. These low-carbon-footprint diets can likely be attributed to a reduced reliance on ruminant meat (cattle and sheep) and processed food consumption, while diets with high carbon footprints are more dependent on ruminant meat and saturated fat. Moderate consumption of meats such as chicken, pork, and fish in conjunction with an emphasis on locally grown fruits and vegetables can be maintained without adversely affecting the planetary carbon footprint and with the added benefit of promoting good health. Thus, making simple substitutions within each individual’s diet can be advertised as an effective approach to collectively lower the environmental impact in tandem with improving health and longevity.