Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single-Layer, Differentially Fed Triband Filtenna With Uniform Polarization and Similar Broadside Radiation Characteristics

An innovative single-layer, differentially fed triband filtenna is presented. It is formed with a main patch, which consists of two interdigitated-coupled driven patches that are approximately mirror-symmetric and four parasitic patches. The strong coupling between the two driven patches facilitates the excitation of the TM<inline-formula> <tex-math notation="LaTeX">$_{\mathbf {1,0}}$ </tex-math></inline-formula>, TM<inline-formula> <tex-math notation="LaTeX">$_{\mathbf {1,2}}$ </tex-math></inline-formula>, TM<inline-formula> <tex-math notation="LaTeX">$_{\mathbf {1,4}}$ </tex-math></inline-formula>, and antiphase TM<inline-formula> <tex-math notation="LaTeX">$_{\mathbf {2,0}}$ </tex-math></inline-formula> modes of the entire main patch and the consequent very small electrical size of the filtenna. Two pairs of open-ended branches are loaded on the main patch to improve the selectivity of the middle band. A pair of split-ring slots are etched on the main patch and four parasitic shorted patches are loaded near it to introduce additional in-band resonances and out-of-band radiation nulls simultaneously, which improve the bandwidth and selectivity of the lower and higher bands, respectively. A prototype was fabricated, assembled, and tested. Its electrical size is <inline-formula> <tex-math notation="LaTeX">$0.31\lambda _{\mathbf {L}} \times 0.28\lambda _{\mathbf {L}} \times 0.031\,\,\lambda _{\mathbf {L}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\lambda _{\mathbf {L}}$ </tex-math></inline-formula> being the free-space wavelength corresponding to the lower band’s center frequency. The experimental results, in agreement with their simulated values, demonstrate operation in three bands: 2.4–2.487, 3.72–3.93, and 5.57–5.88 GHz, with uniform polarization and similar broadside radiation performance. They also show excellent low cross-polarization levels, high common-mode noise immunity, and good filter properties over all three bands.
Multisystem infection by Dipetalonema spp. in a capuchin monkey (Sapajus nigritus)

Abstract The capuchin monkey (Sapajus nigritus) is one of the primates that make up the wild fauna of Rio Grande do Sul. Like other wild animals, primates suffer from infectious diseases transmitted by insects, including filariasis. This report presents the anatomopathological aspects of a multisystemic infection by Dipetalonema spp. in a capuchin monkey, female, adult, of wild origin, rescued along a highway in the north of the state of Rio Grande do Sul by the road policing service and taken for assistance. In the clinical evaluation, nystagmus and involuntary head movements, semi-comatose state, hyperthermia (38.7ºC), hypovolemia, multiple abrasions and deep skin lacerations covering muscle layers were observed. The patient was hospitalized and medicated, but his clinical picture worsened, which resulted in death. At necropsy, the main findings were in the peritoneal cavity, where there was an accumulation of yellowish serous fluid, marked formation of fibrinous adhesions and numerous free nematode parasites in the cavity. Histologically, microfilariae have been observed in the lumen of blood vessels in the lung, liver, heart, kidneys, spleen, small and large intestines, and brain. Peritonitis, pneumonia and bronchiolitis associated with nematodes, liver damage and cerebral microgliosis with satellitosis, neuronophagia and hemorrhagic malacia were also observed. Adult microfilariae and filarids were submitted to morphometric identification and characterized as belonging to the genus Dipetalonema. Thus, it was concluded that this was a case of multisystemic infection by Dipetalonema spp.
Programmable Delay Element Using Dual-Port FeFET for Post-Silicon Clock Tuning

The discovery of ferroelectricity in doped HfO2 has led to its widespread use in various applications, including embedded non-volatile memories and deep learning acceleration. The dual-port FeFET, with separate read and write terminals, has opened up new possibilities for employing tunable threshold voltage transistors in circuits. One such application is the programmable delay element (PDE) used to adjust the delay or frequency based on a control voltage. In this work, we presented a PDE design based on dual-port FeFET that uses the least number of transistors, provides non-volatile storage of the program state, and achieves a wide tuning delay range of 610 ps. Additionally, we demonstrated the application of the proposed PDE in mitigating the effects of circuit aging by selectively adjusting the clock skew of critical path flip-flops. Compared to existing guardband-based approaches, our method achieved a performance gain of approximately 10%.
A New Angle for Explaining the Wave-Particle Duality of Light

The Wave-Particle duality of Light should be considered as an unresolved mystery. Indeed, Light manifests these two very different phenomena simultaneously . On one hand Light should be viewed as a stream of Particles. Einstein initially introduced the understanding that Light should be viewed as a stream of Particles (named Photons), to explain the Photoelectric effect. On the other hand, Light clearly exhibits a Wave facet, dating back to Newton’s days, who measured the wavelength of Li ght with his Newton’s rings interference observations . However, these two very different facets of Light, its Particle facet, and its Wave facet, are so significantly different , which implies that the Wave-Particle duality of Light still awaits additional clarification and additional explanation, which was not yet provided by mainstream Physics. Instead, nowadays mainstream Physics just accepts the fact that Light embed these two very different facets simultaneously , and exhibits each facet in different experiments or situations. This paper proposes a new angle for explaining the Wave-Particle duality of Light, based on the famous Mutual Annihilation process, in which an Electron and a Positron annihilate each other to create Photons, and on the famous inverse Pair Production process, in which a Photon, in certain conditions, converts back into a pair of an Electron and a Positron. Actually, the connection between the nature of Photons and the Electron and the Positron is already presented in another paper, namely, the Electron Positron-Photon idea. The Electron Positron-Photon idea, which is due originally to (the late) Prof. J. P. Wesley, in his paper titled: “Light, a Flux of Electric Dipole Photons” [4], proposed a model of the Photon as an Electric Dipole Photon which might be an Electron-Positron pair separated by a distance L. There are two reasons why the Electron Positron-Photon idea, as presented in Prof. J. P. Wesley's paper, cannot be considered a viable concept:
Lost In The Sands Of Time Somewhere North Of The Bay Of Bengal

In the northeastern portion of the Indian subcontinent, the presence of two language families stretches back into prehistory. What light can historical linguistics, linguistic palaeontology, archaeology, palaeoethnobotany and human population genetics shed on the ancient origins of Austroasiatic and Tibeto-Burman? The world's two most populous families of languages that meet in the Himalayas are the Tibeto-Burman phylum and Indo-European. In addition to these two great linguistic phyla, Kra-Dai alias Daic, Austroasiatic and Dravidian language communities skirt the eastern Himalayan region. The fundamental epistemological question continues to haunt whether the spread of a recognisable Neolithic and Bronze Age assemblage can actually ever be taken with certainty to reflect the spread of a language and so of a language family. Very often language seems to be less ambiguously correlated with the geographical distribution of genetic markers in the populations speaking the languages in question. Keywords: archaeology; human population genetics; Indo-European; linguistic palaeontology; palaeoethnobotany; Tibeto-Burman phylum
Numerical demonstration of a topologically-protected electroacoustic transistor

In this paper we conceptualize electroacoustic transistors based on topologically protected interface states in a reconfigurable valley-Hall topological insulator. Using piezoelectric media and active shunt circuits, we numerically model the spatial inversion symmetry breaking in a unit cell to produce topological bandgaps. These gaps are known to host robust modes for wave propagation along an interface. We use two such modes to design a transistor where the wave propagation in one topological channel switches on or off a second topological channel between a source and receiver elsewhere in the structure. Multiple such transistors may be combined to develop logic gates. Further, we develop and simulate the behavior of an electronic circuit which enables the transistor action. Our design opens a pathway to novel wave-based devices which may find applications in structure-based computing, as hybrid multiplexers in communication devices, and as structural switches or embedded sensors in robotics and internet of things.
A novel bi-level optimization model-based optimal energy scheduling for hybrid ship power system

With the rapid growth of energy consumption and greenhouse gas emissions, the application of traditional ships brings more and more serious pollution problems to the marine environment. For this reason, this paper aims at developing a novel optimal energy scheduling for hybrid ship power system based on bi-level optimization model to reduce fossil fuel consumption and protect the environment. Firstly, a hybrid ship power system model including the diesel generator system, energy storage system, propulsion system, service load system, and photovoltaic generation system is established. Taking the nonlinear and non-convex constraints in solving power generation scheduling and speed scheduling problems into account, an improved genetic algorithm-based bi-level energy optimization strategy is developed. Considering the mileage constraints in coupling constraints, an upper level model for ship energy scheduling is established with the objective of reducing fuel consumption; a lower level optimization model with the goal of minimizing mileage deviation is established through constraint decomposition and fed back to the upper level optimization model. Considering the normal and fault navigation conditions, simulation results verify that the proposed method can significantly minimize operating costs and greenhouse gas emissions by 5.33% and 2.46%, respectively.
Machine Learning CT-Based Automatic Nodal Segmentation and PET Semi-Quantification of Intraoperative 68Ga-PSMA-11 PET/CT Images in High-Risk Prostate Cancer: A Pilot Study

High-resolution intraoperative PET/CT specimen imaging, coupled with prostate-specific membrane antigen (PSMA) molecular targeting, holds great potential for the rapid ex vivo identification of disease localizations in high-risk prostate cancer patients undergoing surgery. However, the accurate analysis of radiotracer uptake would require time-consuming manual volumetric segmentation of 3D images. The aim of this study was to test the feasibility of using machine learning to perform automatic nodal segmentation of intraoperative 68Ga-PSMA-11 PET/CT specimen images. Six (n = 6) lymph-nodal specimens were imaged in the operating room after an e.v. injection of 2.1 MBq/kg of 68Ga-PSMA-11. A machine learning-based approach for automatic lymph-nodal segmentation was developed using only open-source Python libraries (Scikit-learn, SciPy, Scikit-image). The implementation of a k-means clustering algorithm (n = 3 clusters) allowed to identify lymph-nodal structures by leveraging differences in tissue density. Refinement of the segmentation masks was performed using morphological operations and 2D/3D-features filtering. Compared to manual segmentation (ITK-SNAP v4.0.1), the automatic segmentation model showed promising results in terms of weighted average precision (97–99%), recall (68–81%), Dice coefficient (80–88%) and Jaccard index (67–79%). Finally, the ML-based segmentation masks allowed to automatically compute semi-quantitative PET metrics (i.e., SUVmax), thus holding promise for facilitating the semi-quantitative analysis of PET/CT images in the operating room.
Performance Analysis of Logistic Regression, Naive Bayes, KNN, Decision Tree, Random Forest and SVM on Hate Speech Detection from Twitter

- Hate speech specially racism, gender and religion discrimination, defaming comments are becoming one of the biggest problems in Twitter these days, that are making people to switch to other social media. Its effect is long-standing and unpreventable. To stop hateful activities from happening, Machine Learning approaches are needed to be applied. This research article focuses on the performance analysis and effectiveness of Logistic Regression, Gaussian Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest and Support Vector Machine on detection of hate speech from Twitter. SVM, Decision Tree and Random Forest outperformed all the other models, achieving state-of-art 95.5%, 96.2% and 98.2% accuracy respectively on comments gather over a stretch.
Sustainability Management, Technological Innovation and Corporate Social Responsibility for Social Media Small to Medium-Sized Enterprises (SMEs)

The aim of this paper is to investigate the impact of the social and technological environment on business performance. Focus is placed on SMEs and their effort to achieve sustainable competitive advantage and thereby sustainable business performance. For this purpose, a survey study was carried out, where primary data was collected from a representative sample of SMEs operating in the Social Media industry of Greece. Questionnaires were distributed to managers and entrepreneurs of the Social Media Industry. These managers/entrepreneurs were selected using a simple random sampling methodology. The findings of the study revealed that social and technological developments have a major role in developing a sustainable competitive advantage. Strategy alignment was also found to be key in tackling the problems and in undertaking the opportunities that arise from the current social and technological environment, thereby reaching sustainable business performance. The findings of the study are especially useful to entrepreneurs and professionals in the industry in formulating effective strategies towards aligning their business with current advancements in emerging digital technologies. Such an alignment would bring numerous competitive advantages and in turn sustainable business performance.
Toxic Kidney Damage in Rats Following Subchronic Intraperitoneal Exposure to Element Oxide Nanoparticles

Chronic diseases of the urogenital tract, such as bladder cancer, prostate cancer, reproductive disorders, and nephropathies, can develop under the effects of chemical hazards in the working environment. In this respect, nanosized particles generated as by-products in many industrial processes seem to be particularly dangerous to organs such as the testes and the kidneys. Nephrotoxicity of element oxide particles has been studied in animal experiments with repeated intraperitoneal injections of Al2O3, TiO2, SiO2, PbO, CdO, CuO, and SeO nanoparticles (NPs) in total doses ranging from 4.5 to 45 mg/kg body weight of rats. NPs were synthesized by laser ablation. After cessation of exposure, we measured kidney weight and analyzed selected biochemical parameters in blood and urine, characterizing the state of the excretory system. We also examined histological sections of kidneys and estimated proportions of different cells in imprint smears of this organ. All element oxide NPs under investigation demonstrated a nephrotoxic effect following subchronic exposure. Following the exposure to SeO and SiO2 NPs, we observed a decrease in serum creatinine and urea, respectively. Exposure to Al2O3 NPs caused an increase in urinary creatinine and urea, while changes in total protein were controversial, as it increased under the effect of Al2O3 NPs and was reduced after exposure to CuO NPs. Histomorphological changes in kidneys are associated with desquamation of the epithelium (following the exposure to all NPs except those of Al2O3 and SiO2) and loss of the brush border (following the exposure to all NPs, except those of Al2O3, TiO2, and SiO2). The cytomorphological evaluation showed greater destruction of proximal sections of renal tubules. Compared to the controls, we observed statistically significant alterations in 42.1% (8 of 19) of parameters following the exposure to PbO, CuO, and SeO NPs in 21.1% (4 of 19)—following that, to CdO and Al2O3 NPs—and in 15.8% (3 of 19) and 10.5% (2 of 19) of indicators, following the exposure to TiO2 and SiO2 nanoparticles, respectively. Histomorphological changes in kidneys are associated with desquamation of epithelium and loss of the brush border. The cytomorphological evaluation showed greater destruction of proximal sections of renal tubules. The severity of cyto- and histological structural changes in kidneys depends on the chemical nature of NPs. These alterations are not always consistent with biochemical ones, thus impeding early clinical diagnosis of renal damage. Unambiguous ranking of the NPs examined by the degree of their nephrotoxicity is difficult. Additional studies are necessary to establish key indicators of the nephrotoxic effect, which can facilitate early diagnosis of occupational and nonoccupational nephropathies.
Adherence to diabetes risk reduction diet and the risk of head and neck cancer: a prospective study of 101,755 American adults

Background Adherence to the diabetes risk reduction diet (DRRD) may potentially reduce the risk of developing head and neck cancer (HNC) as the diet includes fruits and limits red and processed meats, known risk factors for HNC. However, there is currently no epidemiological research to investigate this potential association. Methods The present study utilized data on demographics, lifestyles, medications, and diets of participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to explore the potential association between adherence to DRRD and the risk of HNC. We used a DRRD score to evaluate adherence to the dietary pattern and employed Cox regression analysis to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for HNC risk. Several subgroup analyses were carried out to identify potential effect modifiers, and multiple sensitivity analyses were performed to evaluate the stability of the correlation. The nine components of the DRRD was assessed separately for its association with the risk of HNC. Results During a mean follow up of 8.84 years, 279 cases of HNC were observed. DDRD score was found to be inversely associated with the risk of HNC (HR Q4 vs. Q1: 0.582; 95% CI: 0.396, 0.856; p = 0.005 for trend) in a linear dose–response manner (p = 0.211 for non-linearity). Subgroup analysis indicated this inverse correlation was more pronounced among participants who had never smoked (HRQ4 vs. Q1: 0.193; 95% CI: 0.073, 0.511; p < 0.001 for trend) compared to current or former smokers (p = 0.044 for interaction). The primary association of DDRD and HNC risk remained robust after several sensitivity analyses. Regarding the individual components of DRRD, an inverse association was also observed between the risk of HNC and increased intake of cereal fiber and whole fruit (all p < 0.05 for trend). Conclusion Our findings provide evidence that following the DRRD pattern may reduce the risk of NHC, especially for non-smokers.
Optimal portfolio choice of couples with tax-deferred accounts and survival-contingent products

Financial products for retirement planning generally have complex taxation structures and death conditions. In particular, tax-deferred accounts (TDAs) can provide tax-sheltered wealth accumulation by deferring taxes, even with the same financial products. Additionally, various survival-contingent products (SCPs), such as annuity products and life insurance contracts, have different payouts for policyholders. In this study, considering both the TDA and SCPs, we formulate and solve a couple’s lifetime portfolio choice problem using a multistage stochastic programming model. Owing to its high-dimensional state space and lifelong planning periods, stochastic dual dynamic programming (SDDP) was used to solve this problem. We find some interesting results; when both the TDA and SCPs are available, the portfolio is less concentrated in annuity holdings than when the TDA is unavailable. Moreover, the couple ends their contribution to the TA earlier than when SCPs are unavailable.
DIG-SLAM: an accurate RGB-D SLAM based on instance segmentation and geometric clustering for dynamic indoor scenes

Simultaneous localization and mapping (SLAM) has emerged as a critical technology enabling robots to navigate in unknown environments, drawing extensive attention within the robotics research community. However, traditional visual SLAM ignores the presence of dynamic objects in indoor scenes, and dynamic point features of dynamic objects can lead to incorrect data correlation, making the traditional visual SLAM is difficult to accurately estimate the camera’s pose when the objects in the scenes are moving. Using only point features cannot fully extract geometric information in dynamic indoor scenes, reducing the system’s robustness. To solve this problem, we develop a RGB-D SLAM system called DIG-SLAM. Firstly, the objects’ contour regions are extracted using the YOLOv7 instance segmentation method, serving as a prerequisite for determining dynamic objects and constructing a semantic information map. Meanwhile, the line features are extracted using the line segment detector algorithm, and the redundant line features are optimized via K-means clustering. Secondly, moving consistency checks combined with instance partitioning determine dynamic regions, and the point and line features of the dynamic regions are removed. Finally, the combination of static line features and point features optimizes the camera pose. Meanwhile, a static semantic octree map is created to provide richer and higher-level scene understanding and perception capabilities for robots or autonomous systems. The experimental results on the Technische Universität München dataset show that the average absolute trajectory error of the developed DIG-SLAM is reduced by 28.68% compared with the dynamic semantic SLAM. Compared with other dynamic SLAM methods, the proposed system shows better camera pose estimation accuracy and system’s robustness in dynamic indoor environments and better map building in real indoor scenes.