Miracle-dz/UniFAR-FTUs huggingface dataset:
Infinite dimensional clarke generalized Jacobian

In this paper we extend for a locally Lipschitz function the notion of Clarke’s generalized Jacobian to the setting where the domain lies in an infinite dimensional normed space. When the function is real-valued this notion reduces to the Clarke’s generalized gradient. Using this extension, we obtain an exact smoothnonsmooth chain rule from which the sum rule and the product rule follow. Also an exact formula for the generalized Jacobian of piecewise differentiable functions will be provided.
Structure From Motion Technique for Scene Detection Using Autonomous Drone Navigation

A method is presented for scene detection and estimation using high-resolution imagery acquired through autonomous drone navigation aided with landmark detection and recognition. The proposed system comprises a drone platform that facilitates efficient autonomous flight; it can capture images and provide real-time video streaming of the ground cover using a camera equipped with a 14-megapixel CMOS sensor and a fish-eye lens. In addition, landmark detection and recognition was performed by applying the histogram of oriented gradients and linear support vector machine methods on each frame of the video stream. The high spatial resolution of the acquired drone images makes the detection and interpretation of environments less complicated. First, through image processing, orthomosaic images and 3-D environment reconstruction (point clouds) of the scene are generated from a set of drone images by using an automatic photogrammetric technique called “structure from motion. ” Subsequently, an unsupervised classification method is used to detect and differentiate environmental classes (scene interpretation) in the target or investigated area by using the high-resolution images. Finally, the results of the proposed method are evaluated by comparing them against ground-truth points.
RIO: Return Instruction Obfuscation for Bare-Metal IoT Devices

The proliferation of IoT comes with many challenges, among which security is one of the most serious issues. Since most IoT devices are designed based on bare-metal devices with low performance, low power, and small form factor, an attacker can easily perform firmware extraction and analysis. In addition, code reuse attacks, such as Return Oriented Programming (ROP) attacks, are possible based on the analyzed firmware information. Since most code reuse attacks are performed through a combination of gadgets that include return instructions, preventing an attacker from analyzing return instructions can be a fundamental solution for these attacks. To prevent code reuse attacks on bare-metal based IoT devices, this paper proposes Return Instruction Obfuscation (RIO). The proposed scheme encrypts all return instructions in the firmware and instruments the modules necessary to decrypt and execute the encrypted return instructions using a Low Level Virtual Machine (LLVM). Since all return instructions in the firmware are encrypted, the proposed scheme can prevent attackers from performing firmware analysis and gadget collection. The proposed scheme was implemented and evaluated on Nuvoton’s NuMaker-PFM-M2351 development board with an ARM Cortex-M23 based SoC.
Multi-frame super resolution robust to local and global motion

Super resolution (SR) is to produce a higher resolution image from one or a sequence of low resolution images of a scene. It is essential in medical image analysis as a zooming of a specific area of interest is often required. This paper presents a new multi-frame super resolution (SR) method that is robust to both global and local motion. One of major challenges in multi-frame SR is concurrent global and local motion emergent in the sequence of low resolution images. It poses difficulties in aligning the low resolution images, resulting in artifacts or blurred pixels in the computed high resolution image. We solve the problem via a series of new methods. We first align the upscaled images from bicubic interpolation, and analyze the pixel distribution for the presence of local motion. If local motion is identified, we conduct the local image registration using dense SIFT features. Based on the local registration of images, we analyze pixel locations whose cross-frame variation is high and adaptively select subset of frame pixels in those locations. The adaptive selection of frame pixels is based on a clustering analysis of luminance values of pixels aligned at the same position, such that noise and motion biases are excluded. At the end, a median filter is applied for the selected pixels at each pixel location for super resolution image. We conduct experiments for multi-frame SR, where the proposed method delivers favorable results, especially better than state-of-the-art in dealing with concurrent local and global motions across frames.
An RC Delay-Based Pressure-Sensing System With Energy-Efficient Bit-Level Oversampling Techniques for Implantable IOP Monitoring Systems

A pressure-sensing system with a half-Wheatstone-bridge-to-digital converter (HBDC) is proposed for implantable intraocular pressure (IOP) monitoring systems. The half-Wheatstone-bridge (H-WhB) sensor uses an RC -delay comparison instead of direct bias of the pressure transducer, allowing it to self-limit the current for efficient operation. To overcome the limited sensitivity of the H-WhB, energy-efficient bit-level oversampling (OS) is introduced. The system achieves 0.24-mmHg (1<inline-formula> <tex-math notation="LaTeX">$\sigma$ </tex-math></inline-formula>) resolution with an 8.58-nJ<inline-formula> <tex-math notation="LaTeX">$\cdot $ </tex-math></inline-formula> mmHg2 FOM and 12.79-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power consumption with a 11.52-ms conversion time. This marks a 2.8<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> improvement in measured system power, 56.24<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> improvement in energy consumption, and 2.8<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> improvement in resolution compared to the prior H-WhB-based pressure sensor. In addition, the HBDC overcomes the low sensitivity limitations of the H-WhB and achieves a resolution FOM comparable to that of Wheatstone-bridge (WhB) sensor-based pressure sensors.
REFERENCE OVERVIEW ON DESIGN AND SIMULATION OF GREEN SUPPLY CHAIN MANAGEMENT

The issue of decreasing air quality index due to supply chain transportation is one of the problems that must be addressed by the manufacturing sector. Green supply chain management (GSCM) can be a solution to address environmental issues in the supply chain. The GSCM is an integrated view that incorporates environmental considerations into the conventional supply chain, ranging from supplier selection, product design, material selection, manufacturing processes, packaging, and distribution. The correct implementation of GSCM can address both environmental and performance issues, e.g. decreasing both energy consumption and air pollution. The GSCM consists of green design, green manufacturing, green logistics, disassembly, and remanufacturing. To address the GSCM issues, the simulation is also discussed in this work. Meanwhile, this work suggests more policies for recycling, remanufacturing, and reuse of obsolete manufacturing products to support GSCM in developing nations.
Heutagogical Approach in Play and Games Courses of Early Childhood in Online Learning

This study aims to describe the use of hetagogy approaches in early childhood play and play courses during the online learning phase in the Early Childhood Islamic Education and Research Program at Sultan Taha Jambi National Islamic University. Because of the COVID-19 pandemic, the lecture process will be conducted via distance learning. This is often called online education. However, the effect of absorbing teaching materials is reduced. Due to the lack of active interaction and being limited to online screens, different learning approaches, such as the hetagogy approach, are being used to re-streamline learning in the online classroom. Has been introduced. This study uses Miles and Huberman's interactive model as a case study of data analysis techniques. Data collection from interviews with 26 students and one lecturer. This research shows that students with a bullish approach encourage more active faculty-student interaction and collaboration, exchange ideas, critical thinking, independence, and successful communication research projects. By doing so, we demonstrate that we are having a positive impact.
Pipette Petri Dish Single-Cell Trapping (PP-SCT) in Microfluidic Platforms: A Passive Hydrodynamic Technique

Microfluidics-based biochips play a vital role in single-cell research applications. Handling and positioning of single cells at the microscale level are an essential need for various applications, including genomics, proteomics, secretomics, and lysis-analysis. In this article, the pipette Petri dish single-cell trapping (PP-SCT) technique is demonstrated. PP-SCT is a simple and cost-effective technique with ease of implementation for single cell analysis applications. In this paper a wide operation at different fluid flow rates of the novel PP-SCT technique is demonstrated. The effects of the microfluidic channel shape (straight, branched, and serpent) on the efficiency of single-cell trapping are studied. This article exhibited passive microfluidic-based biochips capable of vertical cell trapping with the hexagonally-positioned array of microwells. Microwells were 35 μm in diameter, a size sufficient to allow the attachment of captured cells for short-term study. Single-cell capture (SCC) capabilities of the microfluidic-biochips were found to be improving from the straight channel, branched channel, and serpent channel, accordingly. Multiple cell capture (MCC) was on the order of decreasing from the straight channel, branch channel, and serpent channel. Among the three designs investigated, the serpent channel biochip offers high SCC percentage with reduced MCC and NC (no capture) percentage. SCC was around 52%, 42%, and 35% for the serpent, branched, and straight channel biochips, respectively, for the tilt angle, θ values were between 10–15°. Human lung cancer cells (A549) were used for characterization. Using the PP-SCT technique, flow rate variations can be precisely achieved with a flow velocity range of 0.25–4 m/s (fluid channel of 2 mm width and 100 µm height). The upper dish (UD) can be used for low flow rate applications and the lower dish (LD) for high flow rate applications. Passive single-cell analysis applications will be facilitated using this method.
Speaking without Hurting: Assertiveness and Psychological Safety in Receiving Criticism

Receiving criticism for improvement can be difficult, especially when that feedback comes from subordinates. One way to make receiving this information easier is to create a team environment that facilitates addressing these sensitive issues without harming personal relationships. This article analyses two factors that can contribute to channelling this type of criticism: assertiveness and psychological safety. To explore these concepts, we carried out a qualitative study based on semi-structured interviews with team managers. The practices that facilitated receiving criticism from subordinates included speaking respectfully, tolerance for errors, and focusing on the problem rather than the person. In general, receiving this feedback was appreciated and served to strengthen the bond with the other team member.
Two Congeneric Shrubs from the Atacama Desert Show Different Physiological Strategies That Improve Water Use Efficiency under a Simulated Heat Wave

Desert shrubs are keystone species for plant diversity and ecosystem function. Atriplex clivicola and Atriplex deserticola (Amaranthaceae) are native shrubs from the Atacama Desert that show contrasting altitudinal distribution (A. clivicola: 0–700 m.a.s.l.; A. deserticola: 1500–3000 m.a.s.l.). Both species possess a C4 photosynthetic pathway and Kranz anatomy, traits adaptive to high temperatures. Historical records and projections for the near future show trends in increasing air temperature and frequency of heat wave events in these species’ habitats. Besides sharing a C4 pathway, it is not clear how their leaf-level physiological traits associated with photosynthesis and water relations respond to heat stress. We studied their physiological traits (gas exchange, chlorophyll fluorescence, water status) before and after a simulated heat wave (HW). Both species enhanced their intrinsic water use efficiency after HW but via different mechanisms. A. clivicola, which has a higher LMA than A. deserticola, enhances water saving by closing stomata and maintaining RWC (%) and leaf Ψmd potential at similar values to those measured before HW. After HW, A. deserticola showed an increase of Amax without concurrent changes in gs and a significant reduction of RWC and Ψmd. A. deserticola showed higher values of Chla fluorescence after HW. Thus, under heat stress, A. clivicola maximizes water saving, whilst A. deserticola enhances its photosynthetic performance. These contrasting (eco)physiological strategies are consistent with the adaptation of each species to their local environmental conditions at different altitudes.
Design of Metamaterials with Graduating Poisson's Ratio through Periodic Void Patterns

It has been known that when introducing alternating elliptical extrusions in a solid material with a positive Poisson’s Ratio, the material’s effective Poisson’s Ratio can become negative. Furthermore, the change in the effective Poisson’s ratio depends on two factors: the elliptical extrusions’ aspect ratio and the porosity. Using this phenomenon, a study is conducted by combining elliptical extrusions with different aspect ratios and porosity to construct a composite material with gradually varying Poisson’s Ratio. Numerical and physical compression studies are conducted to characterize the material’s effective properties. The results show that the material can effectively stabilize its own structure under unilateral loading and spread out reaction forces. These characteristics make graduating Poisson’s Ratio materials good candidates for impact absorption applications. A brief look at a 3-dimensional auxetic structure is also conducted. A parametric modeling tool for the 3-dimensional structure is created.
Paracomplete Logic K1 ? Natural Deduction, its Automation, Complexity and Applications

In the development of many modern software solutions where the underlying systems are complex, dynamic and heterogeneous, the significance of specification-based verification is well accepted. However, often parts of the specification may not be known. Yet reasoning based on such incomplete specifications is very desirable. Here, paracomplete logics seem to be an appropriate formal setup: opposite to Tarski’s theory of truth with its principle of bivalence, in these logics a statement and its negation may be both untrue. An immediate result is that the law of excluded middle becomes invalid. In this paper we show a way to apply an automatic proof searching procedure for the paracomplete logic Kl to reason about incomplete information systems. We provide an original account of complexity of natural deduction systems, leading us closer to the efficiency of the presented proof search algorithm. Moreover, we have turned the assumptions management into an advantage showing the applicability of the proposed technique to assume-guarantee reasoning.
Hybrid Quantum Encryption Device using Radioactive Decay

The future in how computing is done is heading in the direction of quantum computing given that the space used to store information is finite. Data will eventually be encoded using particles that are on the atomic scale. Objects of these scales are governed by the laws of quantum mechanics. Computing can be done exponentially faster using the properties provided by quantum mechanics. Unfortunately, the increase in computing power creates a security risk for modern encryption standards. Thus, to continue the transfer of data securely one must look to innovative encryption methods that protect information from the speed of quantum computers. This paper is focused on a method that secures information using radioactive decay events in conjunction with an encryption algorithm. The main purpose of this method is the develop an encryption device that holds quantum properties and is interfaceable with a computer system.
Design Approach for FESS-FNSF In-Vessel Components and Constraints Imposed On Radial/Vertical Build Definition

Abstract The Fusion Nuclear Science Facility (FNSF) is an essential element of the U.S. developmental roadmap to fusion energy. The facility displays the complex integration of tokamak components and subsystems in fusion environment while testing and developing fusion technologies for the U.S. demonstration (DEMO) plant. The integration of the neutronics, shielding, and activation assessments is a key element to the success of FNSF operation. This paper overviews the engineering aspects of the tokamak-based FNSF study and presents an integral scheme that considered the overall configuration, radiation limits, top-level design requirements (including maximizing the tritium breeding ratio), smart selection of low-activation materials for each component, radial build optimization and definition, environmental and safety constraints, and upper temperatures for the reuse of reduced activation ferritic martensitic and bainitic structures after severe loss of coolant accidents.
Machine learning-based photometric classification of galaxies, quasars, emission-line galaxies, and stars

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We utilized samples from Sloan Digital Sky Survey (SDSS) Data Release 17 (DR17) and the ALLWISE catalog, which contain spectroscopically labeled sources from SDSS. Our methodology comprises two parts. First, we conducted experiments, including three-class, four-class, and seven-class classifications, employing the Random Forest (RF) algorithm. This phase aimed to achieve optimal performance with balanced datasets. In the second part, we trained various machine learning methods, such as k-nearest neighbors (KNN), RF, XGBoost (XGB), voting, and artificial neural network (ANN), using all available data based on promising results from the first phase. Our results highlight the effectiveness of combining optical and infrared features, yielding the best performance across all classifiers. Specifically, in the three-class experiment, RF and XGB algorithms achieved identical average F1 scores of 98.93 per cent on both balanced and unbalanced datasets. In the seven-class experiment, our average F1 score was 73.57 per cent. Using the XGB method in the four-class experiment, we achieved F1 scores of 87.9 per cent for normal galaxies (NGs), 81.5 per cent for ELGs, 99.1 per cent for stars, and 98.5 per cent for quasars (QSOs). Unlike classical methods based on time-consuming spectroscopy, our experiments demonstrate the feasibility of using automated algorithms on carefully classified photometric data. With more data and ample training samples, detailed photometric classification becomes possible, aiding in the selection of follow-up observation candidates.
MODEL OF DEGENERATE DWARF WITH SPIN-POLARIZED ELECTRON SYSTEM

A three-parametric model of a massive degenerate dwarf was proposed. Unlike paramagnetic state of electron system in the standard Chandrasekhar model electrons are considered in a partially spin-polarized state. The parameters of the model are: x 0 – the relativism parameter at stellar centre, μ e = – the average chemical composition parameter and ζ – the degree of spin polarization of the electron system. The macroscopic characteristics (e.g. mass, radius, energy) as functions of the model parameters were obtained from the solution of the mechanical equilibrium equation. The electron spin polarization was shown to lead to the increase of stellar radius and especially to mass compared with the corresponding characteristics of the standard model. The application of the proposed model to interpreting the stability of massive dwarfs in binary system was discussed.
Presence of Myeloid Mutations in Patients with Chronic Myeloid Leukemia Increases Risk of Cardiovascular Event on Tyrosine Kinase Inhibitor Treatment

Simple Summary Tyrosine kinase inhibitors (TKI), such as imatinib, nilotinib, and dasatinib, are the first-line treatment of choice for patients with chronic myeloid leukemia (CML). However, patients may develop serious cardiovascular events (CVE) with their use. Cardiotoxicity is an important issue given the associated mortality of CVE and the long-term nature of TKI treatment. This study aimed to investigate the association of the presence of somatic myeloid mutations (including those with a reported role in clonal hematopoiesis) at diagnosis and the development of CVE for 102 patients on TKI treatment. The presence of a somatic myeloid mutation was a significant risk factor for CVE on any TKI and shortened the CV event-free survival for patients receiving first-line imatinib treatment. Our work shows that the low risk of CVE, traditionally associated with first-line imatinib, was increased by the presence of myeloid mutations as well as older age. Our findings may help inform first-line TKI choice. Abstract For chronic myeloid leukemia (CML) patients with a known risk of cardiovascular events (CVE), imatinib is often recommended for first-line tyrosine kinase inhibitor (TKI) treatment rather than a second-generation TKI (2G-TKI) such as nilotinib or dasatinib. To date, very few studies have evaluated the genetic predisposition associated with CVE development on TKI treatment. In this retrospective study of 102 CML patients, 26 CVEs were reported during an average follow-up of over 10 years. Next-generation sequencing identified pathogenic/likely pathogenic mutations in genes associated with myeloid malignancies in 24.5% of the diagnostic samples analyzed. Patients with a recorded CVE had more myeloid mutations (0.48 vs. 0.14, p = 0.019) and were older (65.1 vs. 55.7 years, p = 0.016). Age ≥ 60 years and receiving a 2G-TKI in first-line were CVE risk factors. The presence of a pathogenic somatic myeloid mutation was an independent risk factor for CVE on any TKI (HR 2.79, p = 0.01), and significantly shortened the CV event-free survival of patients who received first-line imatinib (by 70 months, p = 0.011). Indeed, 62% of patients on imatinib with mutations had a CVE vs. the 19% on imatinib with a mutation and no CVE. In conclusion, myeloid mutations detectable at diagnosis increase CVE risk, particularly for patients on imatinib, and might be considered for first-line TKI choice.