Miracle-dz/UniFAR-FTUs huggingface dataset:
A Slot-Connected Cavity Design With Corresponding Equivalent Circuit Model Analysis for Fully Metallic 3-D Vivaldi Antenna for Wireless Power Telemetry Applications

This paper presents the design of fully metallic 3D Vivaldi antenna that can be used for wireless power transmission applications. The 3D antenna consists of 1) a tapered profile, 2) a rectangular cavity, and 3) a horizontal slot cut that is used as a transition between the cavity and the tapered profile. The proposed antenna design is fabricated using two distinct approaches, the first of which is a 3D metal additive manufacturing (AM scheme) with a sequential material layer addition technique. The second version is based on the CNC milling (CNCM) technique implemented by selectively removing material in a controlled way. The measured gain of the AM and CNCA-based 3D Vivaldi antenna is 4.95 dBi, and 5.70 dBi, respectively. The measured bandwidth (BW) of the AM-based 3D antenna is 4.70 GHz (fractional BW (FBW) of <inline-formula> <tex-math notation="LaTeX">$52.86\%$ </tex-math></inline-formula>), whereas the CNCM-based 3D antenna is 4.95 GHz (FBW of <inline-formula> <tex-math notation="LaTeX">$56.73\%$ </tex-math></inline-formula>). Measurement outcomes indicate that the CNCM version of the 3D Vivaldi antenna is <inline-formula> <tex-math notation="LaTeX">$\sim ~1.2x$ </tex-math></inline-formula> more effective than the AM version in terms of realized gain and can be used for metal-based antenna system power telemetry due to its high gain and wide operational bandwidth capability.
Symptomatic impact and anxiety generated by
performing pulmonary function tests: Are there
differences between patients with fibrotic interstitial
lung disease and obstructive airway disease?

trend towards greater elevation of cardio-respiratory stress, specially through respiratory rate, was found after PFT in the group of patients with ILD. In contrast, a trend towards higher levels of anxiety immediately before PFT was observed in patients with obstructive disease (mostly COPD) compared to that seen in the group of patients with fibrotic ILD. The variables contributing the most to length of stay in the lung function laboratory were: undergoing a bronchodilation test; the number of attempts needed to reach a technically adequate flow-volume curve; the previous degree of dyspnea, heart rate and respiratory rate before the test; and male gender. A diagnosis of fibrotic ILD was also, by itself, a determining factor for a longer stay in the lab
Short-range constraints on chemical and structural variations in bavenite

Abstract Bavenite is an orthorhombic calcium beryllium aluminosilicate, a ≈ 23.2, b ≈ 5.0, c ≈ 19.4 Å, V ≈ 2250 Å3, Z = 4, that crystallizes in the space group Cmcm. The crystal structures of 24 bavenite samples from various localities worldwide were refined to R1 values from 2.4 to 7.5% based on ~1330 unique reflections collected with Mo-Kα X-radiation on a Bruker P4 CCD single-crystal diffractometer. The composition of each crystal was determined by electron microprobe analysis. There is extensive solid-solution in bavenite according to O(2)OH- + T(4)Si4+ + T(3)Be2+ ⇌ O(2)O2- + T(4)Al3+ + T(3)Si4+, such that the general formula may be written Ca4BexSi9Al4-xO28-x(OH)x, where x ranges from 2.00 to ~3.00 a.p.f.u. Small amounts of additional Be may be incorporated into bavenite via the substitution T(3)Be + O(2)OH- + Na + T(4)Si2 ⇌ T(3)Si + O(2)O2- + Ca + T(4)Al2. Local (short-range) bond-valence considerations indicate that Short-Range Order (SRO) should be extensive in the bavenite structure, and this is confirmed by Fourier Transform Infrared (FTIR) spectroscopy in the principal OH-stretching region and by 27Al Magic Angle Spinning Nuclear Magnetic Resonance (MAS NMR) spectroscopy. Short-range bond-valence considerations indicate that the T(3)-T(4)-T(3)-T(4) rings of the framework can incorporate any short-range arrangement of cations consonant with their site populations [T(3) = Be,Si; T(4) = Si,Al], and 27Al MAS NMR spectroscopy confirms this, showing the presence of the local clusters T(3)Be-T(4)Al-T(3)Be, T(3)Si-T(4)Al-T(3)Be and T(3)Si-T(4)Al-T(3)Si. Incorporation of Be at the T(3) site is accompanied by local replacement of O2- by (OH)- at the O(2) site and hydrogen bonding to the adjacent O(3) anion; the latter promotes Be → Si substitution at the T(3) tetrahedron adjacent in the b direction. T(3)-T(4)-T(3)-T(4) rings link in the c direction through a T(3)-(1)-(3) linkage [T(1) = Si]. Local bond-valence considerations show that occupancy of both T(3) tetrahedra by Be violates the valence-sum rule, and that the linkage T(3)Be-T(1)Si-T(3)Si provides the constraint whereby Be does not exceed 3 a.p.f.u. in bavenite when incorporated via the substitution O(2)OH- + T(4)Si4+ + T(3)Be2+ ⇌ O(2)O2- + T(4)Al3+ + T(3)Si4+.
Antimicrobial Resistance Laboratory Network’s multisite evaluation of the ThermoFisher Sensititre GN7F broth microdilution panel for antimicrobial susceptibility testing

ABSTRACT In 2017, the Centers for Disease Control and Prevention (CDC) established the Antimicrobial Resistance Laboratory Network to improve domestic detection of multidrug-resistant organisms. CDC and four laboratories evaluated a commercial broth microdilution panel. Antimicrobial susceptibility testing using the Sensititre GN7F (ThermoFisher Scientific, Lenexa, KS) was evaluated by testing 100 CDC and Food and Drug Administration AR Isolate Bank isolates [40 Enterobacterales (ENT), 30 Pseudomonas aeruginosa (PSA), and 30 Acinetobacter baumannii (ACB)]. We assessed multiple amounts of transfer volume (TV) between the inoculum and tubed 11-mL cation-adjusted Mueller-Hinton broth: 1 µL [tribe Proteeae (P-tribe) only] and 10, 30, and 50 µL, resulting in respective CFU per milliter of 1 × 104, 1 × 105, 3 × 105, and 5 × 105. Four TV combinations were analyzed: standard (STD) [1 µL (P-tribe) and 10 µL], enhanced standard (E-STD) [1 µL (P-tribe) and 30 µL], 30 µL, and 50 µL. Essential agreement (EA), categorical agreement, major error (ME), and very major error (VME) were analyzed by organism then TVs. For ENT, the average EA across laboratories was <90% for 7 of 15 β-lactams using STD and E-STD TVs. As TVs increased, EA increased (>90%), and VMEs decreased. For PSA, EA improved as TVs increased; however, MEs also increased. For ACB, increased TVs provided slight EA improvements; all TVs yielded multiple VMEs and MEs. For ENT and ACB, Minimum inhibitory concentrations (MICs) trended downward using a 1 or 10 µL TV; there were no obvious MIC trends by TV for PSA. The public health and clinical consequences of missing resistance warrant increased TV of 30 µL for the GN7F, particularly for P-tribe, despite being considered “off-label” use.
Miniature-scale elastocaloric cooling by rubber-based foils

We report on the design and characterization of a demonstrator device for miniature-scale elastocaloric (eC) cooling using a series of natural rubber (NR) foil specimens of 9 × 26.5 mm2 lateral size and thicknesses in the range of 290–900 μm. NR has the potential to meet the various challenges associated with eC cooling, as it exhibits a large adiabatic temperature change in the order of 20 K and high fatigue resistance under dynamic load, while loading forces are low. Owing to the large surface-to-volume ratio of rubber-based foils, heat transfer to heat sink and source elements is accomplished by mechanical contact enabling compact designs. Two actuators are implemented to control the performance in loading direction independent from the performance of mechanical contacting. The study of operation parameters is complemented by lumped-element modeling to understand the cycle frequency-dependent dynamics of heat transfer and resulting cooling capacity. The single-stage device operates in the strain range of 300%–700% and exhibits a temperature span up to 4.1 K, while the specific cooling power reaches 1.1 Wg−1 and the absolute cooling power 123 mW. The performance metrics show a pronounced dependence on foil thickness and heat transfer coefficient indicating a path toward future device optimization.
Molecular survey and phylogenetic analysis of Bartonella sp., Coxiella sp., and hemoplamas in pudu (Pudu puda) from Chile: first report of Bartonella henselae in a wild ungulate species

Introduction Recent evidence shows a high diversity of infectious agents in wildlife that represent a threat to human, domestic, and wild animal health. In Chile, wild populations of the most common cervid species, pudu (Pudu puda), have been reported as hosts for novel pathogens such as Mycoplasma ovis-like and a novel ecotype of Anaplasma phagocytophilum. A better understanding of the epidemiology of this group and other intracellular bacteria that might have cervids as hosts would enlighten their population relevance. This study aimed to determine the occurrence and genetic diversity of Bartonella spp. , hemotropic mycoplasmas, and Coxiella burnetii in pudus from Chile. Methods The DNA was extracted from the blood samples of 69 wild free-ranging and 30 captive pudus from Chile. A combination of real-time (nouG gene for Bartonella and IS1111 element for C. burnetii) and conventional PCR (16S rRNA for hemotropic Mycoplasma spp. and rpoB, gltA, and ITS for Bartonella spp.) was used for pathogen screening and molecular characterization. Results DNA of Bartonella spp. was detected in 10.1% [95% CI (5.2–18.2%)] samples, hemotropic Mycoplasma spp. in 1.7% [95% CI (0.08–10.1%)], and C. burnetii in 1.0% [95% CI (0.05–6.3%)] samples. Two sequenced samples were identified as Mycoplasma ovis-like, and one free-ranging pudu was positive for C. burnetii. While one captive and two free-ranging pudus were positive for Bartonella henselae, one wild pudu was co-positive for B. henselae and Bartonella sp. , similar to Bartonellae identified in ruminants. Discussion To the best of our knowledge, this is the first report of B. henselae in wild ungulate species, and C. burnetii and Bartonella spp. in wild ungulate species in South America. Further research will be necessary to evaluate the potential role of pudu as reservoirs of infection and identify the sources for disease transmission among humans and wild and domestic animals.
Concurrent Negative Impact of Undernutrition and Heart Failure on Functional and Cognitive Recovery in Hip Fracture Patients

Evidence on the effects of frailty, undernutrition, and heart failure (HF) on patients with hip fractures is scarce. This retrospective cohort study aimed to examine the effects of undernutrition and HF on outcomes in patients who underwent convalescent rehabilitation after hip fracture. Undernutrition was defined as body mass index (BMI) < 20.0 (Low BMI). Heart failure (HF) was defined as a B-type natriuretic peptide (BNP) > 100 (High BNP). The study outcomes included the Functional Independence Measure motor domain (FIM-motor) and cognitive domain (FIM-cognition) at discharge. To consider the effects of low BMI, high BNP, and the simultaneous presence of both (“low BMI and high BNP”), we used multivariate linear regression analyses to examine whether these were associated with the outcomes. A total of 110 (mean age 87.4 years, 24.8% male) were analyzed. As a result, low BMI (β = −0.088, p = 0.027) and high BNP (β = −0.053, p = 0.015), each alone, were significantly associated with the FIM motor at discharge, whereas the simultaneous presence of “low BMI and high BNP” was significantly associated with the FIM motor at discharge, while the strength of the association was greater than each association alone (β = −0.152, p = 0.010). Further, the simultaneous presence of “low BMI and high BNP” was significantly associated with FIM cognition at discharge (β = −0.109, p = 0.014). Comprehensive multidisciplinary management is needed, including preoperative or early postoperative nutritional support and rehabilitation, followed by rehabilitation nutrition care management, in patients with hip fracture.
PELATIHAN PENGGUNAAN GOOGLE CLASSROOM BAGI PARA GURU GURU SMP NEGERI 2 RAO KABUPATEN PASAMAN TIMUR SUMATRA BARAT

Belum adanya pelatihan penggunaan Google Classroom dalam kegiatan pembelajaran daring bagi guru SMP Negeri 2 Rao yang disertai dengan kurangnya pengetahuan dan pemahaman tentang cara menggunakan platform pembelajaran daring secara efektif menjadi faktor utama yang melaksanakan pengabdian masyarakat ini. Tujuan dari kegiatan ini adalah melatih guru SMP Negeri 2 Rao untuk menguasai platform pembelajaran daring Google Classroom dalam pembelajaran. Peserta pelatihan ini berjumlah 30 orang guru. Metode yang digunakan dalam pengabdian masyarakat ini adalah pelatihan secara tatap muka dengan melaksanakan protokol kesehatan di masa pandemic ini. Kegiatan pelatihan ini dilaksanakan dalam dua tahap, yaitu: (1) melalui penyajian materi dengan presentasi, diskusi dan tanya jawab; dan (2) melalui tugas praktek dan diskusi pemecahan masalah. Terdapat 89,17% dari 30 guru peserta yang mampu mengoperasikan seluruh Google Classroom setelah pelatihan. Dengan demikian, dari semua tahapan pelaksanaan tersebut para peserta pelatihan berjalan dengan lancar dan materi dapat dipahami dengan baik oleh para peserta pelatihan.
Application of Deep Neural Network with Frequency Domain Filtering in the Field of Intrusion Detection

In the field of intrusion detection, existing deep learning algorithms have limited capability to effectively represent network data features, making it challenging to model the complex mapping relationship between network data and attack behavior. This limitation, in turn, impacts the detection accuracy of intrusion detection systems. To address this issue and further enhance detection accuracy, this paper proposes an algorithm called the Fourier Neural Network (FNN). The core of FNN consists of a Deep Fourier Neural Network Block (DFNNB), which is composed of a Hadamard Neural Network (HNN) and a Fourier Neural Network Layer (FNNL). In a DFNNB, the HNN is responsible for sampling the network intrusion data samples in different time domain spaces. The FNNL, on the other hand, performs a Fourier transform on the samples outputted by the HNN and maps them to the frequency domain space, followed by a filtering process. Finally, the data processed by filtering are transformed back to the time domain space for subsequent feature extraction work by the DFNNB. Additionally, to enhance the algorithm’s detection accuracy and filter out noise signals, this paper also introduces a High-energy Filtering Process (HFP), which eliminates noise signals from the data signal and reduces interference on the final detection result. Due to the ability of FNN to process network data in both the time domain space and the frequency domain space, it possesses a stronger capability in expressing data features. Finally, this paper conducts performance evaluations on the KDD Cup99, NSL-KDD, UNSW-NB15, and CICIDS2017 datasets. The results demonstrate that the proposed FNN-based IDS model achieves higher detection rates, lower false alarm rates, and better detection performance than classical deep learning and machine learning methods.
Multistep Look-Ahead Policy Iteration for Optimal Control of Discrete-Time Nonlinear Systems With Isoperimetric Constraints

In this article, a novel multistep look-ahead policy iteration with isoperimetric constraints (MLPIIC) method is developed to solve infinite horizon optimal control problems (OCPs) with isoperimetric constraints for discrete-time nonlinear systems. In order to overcome the difficulty that Bellman’s principle of optimality does not hold directly in OCPs with isoperimetric constraints, a method to approximate OCPs with isoperimetric constraints by OCPs with new constraints is developed. For the MLPIIC method initialized with an admissible control law, the convergence and optimality of the iterative value function and the feasibility of the iterative control law are proven. Utilizing the function approximator, the implementation of the MLPIIC method is described. Finally, simulation results are provided.
Loss of CFTR function in macrophages alters the cell transcriptional program and delays lung resolution of inflammation

Cystic fibrosis (CF) is an autosomal recessive genetic disorder caused by mutations in the CF Transmembrane-conductance Regulator (CFTR) gene. The most severe pathologies of CF occur in the lung, manifesting as chronic bacterial infection, persistent neutrophilic inflammation, and mucopurulent airway obstruction. Despite increasing knowledge of the CF primary defect and the resulting clinical sequelae, the relationship between the CFTR loss of function and the neutrophilic inflammation remains incompletely understood. Here, we report that loss of CFTR function in macrophages causes extended lung inflammation. After intratracheal inoculation with Pseudomonas aeruginosa, mice with a macrophage-specific Cftr-knockout (Mac-CF) were able to mount an effective host defense to clear the bacterial infection. However, three days post-inoculation, Mac-CF lungs demonstrated significantly more neutrophil infiltration and higher levels of inflammatory cytokines, suggesting that Mac-CF mice had a slower resolution of inflammation. Single-cell RNA sequencing revealed that absence of CFTR in the macrophages altered the cell transcriptional program, affecting the cell inflammatory and immune responses, antioxidant system, and mitochondrial respiration. Thus, loss of CFTR function in macrophages influences cell homeostasis, leading to a dysregulated cellular response to infection that may exacerbate CF lung disease.
Similarity Distance Learning on SPD Manifold for Writer Independent Offline Signature Verification

Identifying the existence or approval of a human in a number of past, recent and present day activities with the use of a handwritten signature is a captivating biometric challenge. Several engineering branches such as computer vision, pattern recognition and quite recently data-driven machine learning algorithms are combined in a multi-disciplined signature verification framework in order to deliver an equivalent and efficient e-assistance to manually executed duties, which usually demand knowledge and skills. In this work, we propose, for the first time, the use of a learnable Symmetric Positive Definite manifold distance framework in offline signature verification literature in order to build a global writer-independent signature verification classifier. The key building block of the framework relies on the use of regional covariance matrices of handwritten signature images as visual descriptors, which maps them into the Symmetric Positive Definite manifold. The learning and verification protocol explores both blind intra and blind inter transfer learning frameworks with the use of four popular signature datasets of Western and Asian origin. Experiments strongly indicate that the learnable SPD manifold similarity distance can be highly efficient for offline writer independent signature verification.
Association between Pulmonary Aspergillosis and Cytomegalovirus Reactivation in Critically Ill COVID-19 Patients: A Prospective Observational Cohort Study

COVID-19-associated invasive pulmonary aspergillosis (CAPA) is common and is associated with poor outcomes in critically ill patients. This prospective observational study aimed to explore the association between CAPA development and the incidence and prognosis of cytomegalovirus (CMV) reactivation in critically ill COVID-19 patients. We included all consecutive critically ill adult patients with confirmed COVID-19 infection who were admitted to three COVID-19 intensive care units (ICUs) in an Italian hospital from 25 February 2020 to 8 May 2022. A standardized procedure was employed for early detection of CAPA. Risk factors associated with CAPA and CMV reactivation and the association between CMV recurrence and mortality were estimated using adjusted Cox proportional hazard regression models. CAPA occurred in 96 patients (16.6%) of the 579 patients analyzed. Among the CAPA population, 40 (41.7%) patients developed CMV blood reactivation with a median time of 18 days (IQR 7–27). The CAPA+CMV group did not exhibit a significantly higher 90-day mortality rate (62.5% vs. 48.2%) than the CAPA alone group (p = 0.166). The CAPA+CMV group had a longer ICU stay, fewer ventilation-free days, and a higher rate of secondary bacterial infections than the control group of CAPA alone. In the CAPA population, prior immunosuppression was the only independent risk factor for CMV reactivation (HR 2.33, 95% C.I. 1.21–4.48, p = 0.011). In critically ill COVID-19 patients, CMV reactivation is common in those with a previous CAPA diagnosis. Basal immunosuppression before COVID-19 appeared to be the primary independent variable affecting CMV reactivation in patients with CAPA. Furthermore, the association of CAPA+CMV versus CAPA alone appears to impact ICU length of stay and secondary bacterial infections but not mortality.
On Input Generators for Cyber–Physical Systems Falsification

Falsification is a testing method that aims to increase confidence in the correctness of cyber–physical systems by guiding the search for counterexamples with some optimization algorithm. This method generates input signals for a simulation of the system under test and employs quantitative semantics, which serves as objective functions, to minimize the distance needed to falsify a specification. Various implementations based on different optimization strategies and semantics have been proposed and evaluated in the past. Generally, they assume that an input generator is given. However, this is often not the case in practice and different choices can lead to vastly different outcomes. Therefore, this article introduces and evaluates various parameterizations of input generators, including pulse, sinusoidal, and piecewise signals with different interpolation techniques. These input generators are compared based on their performance on benchmark examples, as well as coverage measures in the space-time and frequency domains. Input generators facilitate the exploration of numerous different input signals within a single falsification problem, making them especially valuable for industrial practitioners seeking to incorporate falsification into their daily development work.
Rancang Bangun Aplikasi Indexing Al-Qur`an pada Platform Windows Phone

Al-Quran terdiri dari 30 Juz, 114 Surat dan 6,236 Ayat, dan Al-Quran yang ada saat ini dibuat secara lengkap dan berurutan dimulai dari Surat Al Fatihah dan diakhiri dengan Surat Annas menyesuaikan naskah asalnya, sehingga jika seseorang ingin mencari sebuah ayat atau dalil dalam Al-Quran sesui topik yang diinginkan maka harus membuka Al-Quran dan mencarinya satu persatu dari awal sampai akhir. Hal ini cukup memakan waktu lama dan pasti akan menemukan banyak kesulitan dengan banyaknya lembaran dan banyaknya nama-nama surat dan ayat-ayat yang ada didalamnya, terlebih bagi orang yang baru belajar Islam dan masih awam tentang Al-Quran. Dengan hadirnya Aplikasi indexing Al-Quran berbasis windows phone ini diharapkan dapat memberikan solusi untuk mempermudah dan mempercepat untuk menemukan sebuah ayat yang diperlukan. Hanya dengan mengetikkan judul tema yang akan dicari, aplikasi ini dapat dengan langsung memunculkan nomor surat dan ayat juga menampilkan ayat dalam teks Arab dan terjemahan dalam Bahasa Indonesia secara bersamaan.