Miracle-dz/UniFAR-FTUs huggingface dataset:
Indonesian Waste Database: Smart Mechatronics System

Waste management is an essential component of urban management. As a waste solution, waste management is critical. The goal of this research is to develop a waste management database that is coupled with a mechatronic robot system. Compiling and gathering data on the sorts of garbage found in Indonesia is the starting point for this research. Indonesian waste is classified into six groups: cardboard, paper, metal, plastic, medical, and organic. The total images of the six groups are estimated at 1880 pictures. According to this picture database, Artificial Intelligence (AI) training was used to create the classification system. In the final AI process, the test method was performed using DenseNet121, DenseNet169, and DenseNet201. Testing using artificial intelligence DenseNet201 across 40 epochs yields the best 92,7% accuracy rate. Simultaneously with Artificial Intelligence testing, a mechatronic system is created as a direct implementation of the Artificial Intelligence output model. A four-servo arm robot with dc motor wheel mobility is included in the mechatronic system. According to these findings, the Indonesian waste database can be categorized correctly using Artificial Intelligence and the mechatronics system. This higher accuracy of the artificial intelligence model may be used to create a waste-sorting robot prototype.
Scanning slot cone-beam computed tomography and scanning focus spot cone-beam computed tomography

A method of imaging an object that includes directing a plurality of x-ray beams in a fan-shaped form towards an object, detecting x-rays that pass through the object due to the directing a plurality of x-ray beams and generating a plurality of imaging data regarding the object from the detected x-rays. The method further includes forming either a three-dimensional cone-beam computed tomography, digital tomosynthesis or Megavoltage image from the plurality of imaging data and displaying the image.
Multisensory Stimulation Reverses Memory Impairment in Adrβ3KO Male Mice

Norepinephrine plays an important role in modulating memory through its beta-adrenergic receptors (Adrβ: β1, β2 and β3). Here, we hypothesized that multisensory stimulation would reverse memory impairment caused by the inactivation of Adrβ3 (Adrβ3KO) with consequent inhibition of sustained glial-mediated inflammation. To test this, 21- and 86-day-old Adrβ3KO mice were exposed to an 8-week multisensory stimulation (MS) protocol that comprised gustatory and olfactory stimuli of positive and negative valence; intellectual challenges to reach food; the use of hidden objects; and the presentation of food in ways that prompted foraging, which was followed by analysis of GFAP, Iba-1 and EAAT2 protein expression in the hippocampus (HC) and amygdala (AMY). The MS protocol reduced GFAP and Iba-1 expression in the HC of young mice but not in older mice. While this protocol restored memory impairment when applied to Adrβ3KO animals immediately after weaning, it had no effect when applied to adult animals. In fact, we observed that aging worsened the memory of Adrβ3KO mice. In the AMY of Adrβ3KO older mice, we observed an increase in GFAP and EAAT2 expression when compared to wild-type (WT) mice that MS was unable to reduce. These results suggest that a richer and more diverse environment helps to correct memory impairment when applied immediately after weaning in Adrβ3KO animals and indicates that the control of neuroinflammation mediates this response.
Phenolic Content and Antioxidant Activity of Centella asiatica L. in Response to Organic and Chemical Fertilizer

Background: Centella asiatica L. is a traditional medicinal plant popular in several Asian countries. The cultivation of this herb is facing the problem of overuse of chemical fertilizers and quality deterioration. The aim of this study was to evaluate the effect of organic and non-organic fertilizer on growth, yield and phytochemical content of centella. Methods: The set-up was performed in the field from June to November 2021. The treatments were: no fertilizer (control); inorganic fertilizer (the famer’s recommended rate; 150 kg N ha-1:50 kg P ha-1: 50 kg K ha-1); organic compost (10 tones ha-1); inorganic fertilizer (a half of recommendation rate; 75 kg N ha-1:25 kg P ha-1: 25 kg K ha-1);organic compost (5 tones ha-1) plus inorganic fertilizer (a half of recommendation rate; 100 kg N ha-1:25 kg P ha-1: 25 kg K ha-1). Result: The application of fertilizer increased the plant growth, biomass production and total chlorophyll content of centella. Nonetheless, the high amount of inorganic fertilizer led to a reduction in the phytochemical content and antioxidant activity in centella leaf. The combination of organic compost and inorganic fertilizer produced maximum growth and increased the total phenolic content and antioxidant activity.
The Impact of MiR-33a-5p Inhibition in Pro-Inflammatory Endothelial Cells

Evidence suggests cholesterol accumulation in pro-inflammatory endothelial cells (EC) contributes to triggering atherogenesis and driving atherosclerosis progression. Therefore, inhibiting miR-33a-5p within inflamed endothelium may prevent and treat atherosclerosis by enhancing apoAI-mediated cholesterol efflux by upregulating ABCA1. However, it is not entirely elucidated whether inhibition of miR-33a-5p in pro-inflammatory EC is capable of increasing ABCA1-dependent cholesterol efflux. In our study, we initially transfected LPS-challenged, immortalized mouse aortic EC (iMAEC) with either pAntimiR33a5p plasmid DNA or the control plasmid, pScr. We detected significant increases in both ABCA1 protein expression and apoAI-mediated cholesterol efflux in iMAEC transfected with pAntimiR33a5p when compared to iMAEC transfected with pScr. We subsequently used polymersomes targeting inflamed endothelium to deliver either pAntimiR33a5p or pScr to cultured iMAEC and showed that the polymersomes were selective in targeting pro-inflammatory iMAEC. Moreover, when we exposed LPS-challenged iMAEC to these polymersomes, we observed a significant decrease in miR-33a-5p expression in iMAEC incubated with polymersomes containing pAntimR33a5p versus control iMAEC. We also detected non-significant increases in both ABCA1 protein and apoAI-mediated cholesterol in iMAEC exposed to polymersomes containing pAntimR33a5p when compared to control iMAEC. Based on our results, inhibiting miR-33a-5p in pro-inflammatory EC exhibits atheroprotective effects, and so precisely delivering anti-miR-33a-5p to these cells is a promising anti-atherogenic strategy.
Hematopoiesis and Mast Cell Development

Hematopoietic stem cells (HSCs) are defined based on their capacity to replenish themselves (self-renewal) and give rise to all mature hematopoietic cell types (multi-lineage differentiation) over their lifetime. HSCs are mainly distributed in the bone marrow during adult life, harboring HSC populations and a hierarchy of different kinds of cells contributing to the “niche” that supports HSC regulation, myelopoiesis, and lymphopoiesis. In addition, HSC-like progenitors, innate immune cell precursors such as macrophages, mast cells, natural killer cells, innate lymphoid cells, and megakaryocytes and erythrocyte progenitor cells are connected by a series of complex ontogenic relationships. The first source of mast cells is the extraembryonic yolk sac, on embryonic day 7. Mast cell progenitors circulate and enter peripheral tissues where they complete their differentiation. Embryonic mast cell populations are gradually replaced by definitive stem cell-derived progenitor cells. Thereafter, mast cells originate from the bone marrow, developing from the hematopoietic stem cells via multipotent progenitors, common myeloid progenitors, and granulocyte/monocyte progenitors. In this review article, we summarize the knowledge on mast cell sources, particularly focusing on the complex and multifaceted mechanisms intervening between the hematopoietic process and the development of mast cells.
Phosphorus May Induce Phenotypic Transdifferentiation of Vascular Smooth Muscle Cells through the Reduction of microRNA-145

Phosphorus is a vital element for life found in most foods as a natural component, but it is also one of the most used preservatives added during food processing. High serum phosphorus contributes to develop vascular calcification in chronic kidney disease; however, it is not clear its effect in a population without kidney damage. The objective of this in vivo and in vitro study was to investigate the effect of high phosphorus exposure on the aortic and serum levels of miR-145 and its effect on vascular smooth muscle cell (VSMCs) changes towards less contractile phenotypes. The study was performed in aortas and serum from rats fed standard and high-phosphorus diets, and in VSMCs exposed to different concentrations of phosphorus. In addition, miR-145 silencing and overexpression experiments were carried out. In vivo results showed that in rats with normal renal function fed a high P diet, a significant increase in serum phosphorus was observed which was associated to a significant decrease in the aortic α-actin expression which paralleled the decrease in aortic and serum miR-145 levels, with no changes in the osteogenic markers. In vitro results using VSMCs corroborated the in vivo findings. High phosphorus first reduced miR-145, and afterwards α-actin expression. The miR-145 overexpression significantly increased α-actin expression and partially prevented the increase in calcium content. These results suggest that miR-145 could be an early biomarker of vascular calcification, which could give information about the initiation of the transdifferentiation process in VSMCs.
Cryptanalysis on Hash Functions Based on Ramanujan Graphs

Hash function is a fundamental tool in cryptography. In December 15th, 2016, The National Institute of Standards and Technology (NIST) announced that they accept submissions for post-quantum candidate algorithms. NIST asked cryptographists to develop cryptographic systems that are secure against both quantum and classical computers, and can interoperate with existing communications protocols and networks. According to their report on post-quantum cryptography, for hash functions against impact from large-scale quantum computer, it needs larger output. Cayley hash functions are a family of cryptographic hash functions constructed from Cayley graphs, with appealing properties such as a natural parallelism and a security reduction to a clean, well-defined mathematical problem. As this problem involves non-Abelian groups, it is a priori resistant to quantum period finding algorithms and Cayley hash functions may therefore be a good foundation for post-quantum cryptography. LPS hash functions, which are constructed as a random walk based on the optimal expander graphs of Lubotzky, Phillips and Sarnak, were proposed by Charles, Goren and Lauter at Journal of Cryptology in 2009. Finding collisions of Cayley hash functions is finding cycles in their based graphs. It implies that finding a non-trivial factorization of the identity in relation to some particular elements of a projective group of matrices. Tillich and Zèmor exhibited an algorithm for finding collisions of LPS hash functions that runs in time quasi-linear n, where n is the hashcode size.
Effect of Dietary Supplements Which Upregulate Nitric Oxide on Walking and Quality of Life in Patients with Peripheral Artery Disease: A Meta-Analysis

This systematic review pooled evidence from randomised controlled trials (RCTs) on the effectiveness of dietary upregulators of nitric oxide (NO) in improving the walking and quality of life of patients with peripheral artery disease (PAD). RCTs examining the effect of dietary upregulators of NO in patients with PAD were included. The primary outcome was the maximum walking distance. Secondary outcomes were the initial claudication distance, the six-minute walking distance, quality of life, the ankle-brachial pressure index (ABI), adverse events and risk of mortality, revascularisation or amputation. Meta-analyses were performed using random effects models. The risk of bias was assessed using Cochrane’s ROB-2 tool. Leave-one-out and subgroup analyses were conducted to assess the effect of individual studies, the risk of bias and intervention type on pooled estimates. Thirty-four RCTs involving 3472 participants were included. Seven trials tested NO donors, nineteen tested antioxidants, three tested NO synthase inducers and five tested enhancers of NO availability. Overall, the dietary supplements significantly improved the initial claudication (SMD 0.34; 95%CI 0.04, 0.64; p = 0.03) but not maximum walking (SMD 0.13; 95%CI −0.17, 0.43; p = 0.39) distances. Antioxidant supplements significantly increased both the maximum walking (SMD 0.36; 95%CI 0.14, 0.59; p = 0.001) and initial claudication (SMD 0.58; 95%CI 0.26, 0.90; p < 0.001) distances. The dietary interventions did not improve the physical function domain of the Short Form-36 (SMD −0.16; 95%CI −0.32, 0.00; p = 0.38), ABI or risk of adverse events, mortality, revascularisation or amputation. Dietary NO upregulators, especially antioxidants, appear to improve the initial claudication distance in patients with PAD. Larger high-quality RCTs are needed to fully examine the benefits and risks of these treatments. PROSPERO Registration: CRD42022256653.
Estimation Method for Residual Sodium Amount on Unloaded Dummy Fuel Assembly

Abstract This study has researched an estimation method for the amounts of residual sodium film and sodium lumps on dummy fuel pins in the Japanese prototype fast breeder reactor Monju by fundamental experiments and demonstration experiments. The residual sodium amounts on the pin surface were measured using three types of test specimens: (a) single pin, (b) 7-pin assembly, and (c) 169-pin assembly. The single pin and 7-pin assembly experiments revealed that the withdrawal speed of the pins and improvement of the sodium wetting drastically increased the residual sodium amounts. Furthermore, the 169-pin assembly experiments measured the practical amounts of the residual sodium in the Monju dummy fuel assembly and demonstrated sodium draining behavior through small gaps between the pins. The estimation method includes four models such as a viscosity flow model, Landau-Levich-Derjaguin (LLD) model, an empirical equation related to the Bretherton model, and a capillary force model in a tube. These calculation results were comparable to the residual sodium amounts obtained by the experiments. In the tests of improving sodium wetting, the amounts of residual sodium on the test specimen were close to 1.4 times larger than those of the thin sodium film estimated by the LLD model. The increased amount of residual sodium by improving the sodium wetting was explained by the ratio of the adhesion energy ($${\gamma _{SO}} - {\gamma _{SL}}$$γSO−γSL).
Robust Decentralized H∞ Attack-Tolerant Observer-Based Team Formation Network Control of Large-Scale Quadrotor UAVs: HJIE-Reinforcement Learning-Based Deep Neural Network Method

In this paper, a robust decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based team formation tracking control scheme is proposed for large-scale quadrotor unmanned aerial vehicle (UAV) systems under external disturbance, measurement noise, couplings from other neighboring quadrotor UAVs, and malicious attacks on actuator and sensor of the network control system (NCS) via wireless communication. First, we constructed a smoothed model of attack signals to describe their behavior. Then, by integrating the smoothed dynamic model with the system dynamic model of each quadrotor UAV, we can simultaneously estimate the attack signals and the system state of each quadrotor UAV through a traditional Luenberger observer for the efficient robust decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based team formation tracking control of large-scale quadrotor UAVs. For the design of robust decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based team formation tracking control of large-scale quadrotor UAVs, a very difficult independent nonlinear partial differential observer/controller-coupled Hamilton Jacobi Issac equation (HJIE) must be solved for the observer and controller design of each quadrotor UAV. Nowadays, there are no analytical and numerical methods to resolve HJIE. Thus, an HJIE-reinforcement learning-based deep neural network (DNN) is trained to directly solve the observer/controller-coupled HJIE for robust decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based team formation tracking control of each quadrotor UAV. Since the system model of the quadrotor UAV and HJIE have been adopted for the HJIE-reinforcement Adam learning algorithm DNN training, compared to the traditional DNN big data-driven training schemes, we save a lot of training data and time to achieve the robust decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based team formation tracking control design. As the Adam algorithm converges, we could show that the proposed HJIE-reinforcement DNN-based decentralized <inline-formula> <tex-math notation="LaTeX">$H_{\infty} $ </tex-math></inline-formula> attack-tolerant observer-based tracking control scheme can achieve the theoretical result. Finally, the simulation results are presented with a comparison to verify the effectiveness of the proposed method.
A Comparative Study on Optimization Techniques for Solving Multi-objective Geometric Programming Problems

Various optimization techniques are there for mathematical modeling and design of many non-linear problems related to the various eld of science and engineering. The real world engineering problems are occurring in the form of multi-criteria having certain constraints. Till now, no such single optimization method exist which could optimize all objective functions simultaneously. In this paper, weighted sum method has been discussed to solve multi-objective geometric programming problem(MOGPP) and the result so obtained by weighted sum method has been compared with fuzzy programming method. Illustrative examples are presented to demonstrate the correctness of proposed model.
Functional fabrics for multilayered textile pressure sensors: comparison of structures and sensitivity characteristics

In the field of protective smart clothing, such topics as monitoring of wearer’s vital signs and spatial position are thoroughly studied in the literature. On the other hand, solutions for monitoring of hazardous events, such as high-energy impacts with foreign objects are studied to less extent. Such protective clothing is intended both for operators, working in environments with a risk of injury due to impact with moving parts or falling objects, e.g. operators of heavy agricultural machinery, first responders etc. Such a sensor would enable to detect the location of the impact, its force and would allow to develop a system that sends appropriate emergency signals. The proposed paper focuses on the development of such a sensor, giving a special attention to its structure and usable materials. The proposed matrix array sensor consists of three layers: upper and lower layers with electrically conductive traces and the intermediate piezoresistive layer. Due to the intended application, a textile piezoresistive layer is chosen and after studying the commercially available materials, EeonTex LTT-SLPA 60 kOhm conductive polymer-coated knitted fabric and Sefar Carbotex 03-120CF, 03-160CF and 03-205CF carbon/polyester woven fabrics were selected as the most suitable candidates for further testing. The testing was accomplished using Zwick/Roell Z2.5 compression/strain testing column and Agilent A34970A ohmmeter. The testing focused on changes in fabrics’ conductivity under cyclic stress, sensitivity, measurement hysteresis and repeatability. Different technologies for connecting the piezoresistive and the outside layers were tested as well: direct connection and connection using conductive adhesive textile tapes. Based on the results obtained during testing, recommendations are given for the usage of the studied materials, based on their performance under various levels of stress. During the experiments the best metrological results were demonstrated by piezoresistive fabrics with conductive polymer coating. Besides that, it was concluded that while hot-melt adhesive conductive tapes substantially degrade the sensors’ properties, the use of self-adhesive conductive tapes ensure constant and stable contact between the sandwich layers and thus improve the measuring stability.
Effects of graphene quantum dots on linear and nonlinear optical behavior of malignant ovarian cells

Abstract. We investigate linear and nonlinear optical properties of standard human ovarian cancer cells (cell line: A2780cp) in vitro. Cells were treated by graphene quantum dots (GQDs) with two special concentrations. Nontoxicity of GQDs was examined in standard biological viability tests. Cancerous cells were fixed on a glass slide; then, interaction of light with biofilms was studied in linear and nonlinear regimes. Absorption spectra of untreated biofilms and biofilms with two different concentrations of GQDs was studied by UV-visible spectrophotometer. Optical behavior of biofilms in a linear regime of intensity (with low-intensity laser exposure) was reported using a simple optical setup. After that, we compared the attenuation of light in biofilm of cancerous cells with and without GQDs. Nonlinear behavior of these biofilms was investigated by a Z-scan setup using a continued wave He–Ne laser. Results showed that GQDs decreased the extinction coefficient and changed the sign and exact value of the nonlinear refractive index of malignant ovarian cells noticeably. The nonlinear refractive index of studied cells with no GQDs treatment was in the order of 10−8 (cm2/w) with a positive sign. This quantity changed to the same order of magnitude with a negative sign after GQDs treatment. Thus, GQDs can be used for cancer diagnosis under laser irradiation.
Lattice Boltzmann Method and Its Applications in Soft Matter

Transport phenomena in biological flow and soft matter is very important in understanding human disease and health. The interaction between cells and blood plasma is important because it not only shows complex mechanical behavior but also advance our knowledge in medical research. This dissertation presents modeling work in drug carrier delivery in blood suspensions and early detection of circulating tumor cells. Methodologically, the Lattice Boltzmann method (chapter 2) was employed as Navier-Stokes fluid solver due to its competence in modeling single phase and multiphase flow, handling complex geometries, and the capacity in parallel computing. A significant part of the work was devoted to the theory, algorithm, boundary conditions, and code implementations. The cells were implemented using a coarse grained molecular dynamics model (chapter 3) because of its capacity in modeling solid nonlinear large deformations. Besides the suspending fluid and cells, nanoparticles (drug carriers) were also introduced into the system (chapter 4). The coupling fluid and solid was based on the Immersed Boundary Method (chapter 5) which removes the burden of expensive mesh updating in traditional Arbitrary Lagrangian Eulerian approach. The developed code was validated for lid driven cavity flow, cell stretching test, and sphere dropping test in a quiescent fluid. Numerical models were created to study nanoparticle transport in blood cell suspensions(chapter 6). Nanoparticle (NP) dispersion rate is found to be strongly influenced by Red blood cell (RBC) motion, and to have an approximately linear relationship with shear rate in the