Miracle-dz/UniFAR-FTUs huggingface dataset:
Modular multiplication without trial division

Let N > 1. We present a method for multiplying two integers (called N-residues) modulo N while avoiding division by N. N-residues are represented in a nonstandard way, so this method is useful only if several computations are done modulo one N. The addition and subtraction algorithms are unchanged. 1. Description. Some algorithms (1), (2), (4), (5) require extensive modular arith- metic. We propose a representation of residue classes so as to speed modular multiplication without affecting the modular addition and subtraction algorithms. Other recent algorithms for modular arithmetic appear in (3), (6). Fix N > 1. Define an A'-residue to be a residue class modulo N. Select a radix R coprime to N (possibly the machine word size or a power thereof) such that R > N and such that computations modulo R are inexpensive to process. Let R~l and N' be integers satisfying 0 N then return t - N else return t ■ To validate REDC, observe mN = TN'N = -Tmod R, so t is an integer. Also, tR = Tmod N so t = TR'X mod N. Thirdly, 0 < T + mN < RN + RN, so 0 < t < 2N. If R and N are large, then T + mN may exceed the largest double-precision value. One can circumvent this by adjusting m so -R < m < 0. Given two numbers x and y between 0 and N - 1 inclusive, let z = REDC(xy). Then z = (xy)R~x mod N, so (xR-l)(yR~x) = zRx mod N. Also, 0 < z < N, so z is the product of x and y in this representation. Other algorithms for operating on N-residues in this representation can be derived from the algorithms normally used. The addition algorithm is unchanged, since xR~x + yR~x = zR~x mod N if and only if x + y = z mod N. Also unchanged are
Green Honey Deli Water Apple (Syzygium aqueum (Burm. f.) Alston “Madu Deli Hijau”): Evaluation of Antioxidant Activities and Phytochemical Content

BACKGROUND OF THE STUDY: Antioxidants are able to fight against free radicals which then prevent degenerative diseases. Antioxidants can be found in many plants such as water apples. AIM OF THE STUDY: This research is aimed to determine the antioxidant activity of green honey deli water apple (Syzygium aqueum) leaves, branches, fruits extracts through 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Cupric Reducing Antioxidant Capacity (CUPRAC) methods, total phenolic content (TPC), total flavonoid content (TFC), correlation of TPC and TFC on antioxidant activity, correlation between DPPH and CUPRAC methods, and content of flavonoid compounds found in ethanol fruit extract of green honey deli water apple. METHODOLOGY: Antioxidant activities were examined by determining ascorbic acid equivalent (AAE) through DPPH and CUPRAC methods. TPC and TFC were determined using UV-vis spectrophotometry. Correlation of TPC and TFC on antioxidant activity and correlation between DPPH and CUPRAC results were analyzed by Pearson’s method. Contents of flavonoid compounds were determined using HPLC. RESULTS: Antioxidant activities of green honey deli water apple leaves, branches, and fruits extracts according to DPPH and CUPRAC methods were 3.97–354.96 mg AAE/g; 10.46–222.51 mg AAE/g respectively. Ethanol leaves extract had the highest TPC (68.14 ± 1.69 g GAE/100 g) and ethyl acetate leaves extract showed the highest TFC (18.65 ± g QE/100 g). TPC and TFC were found to correlate with the antioxidant activities. DPPH and CUPRAC results also correlated significantly positive. CONCLUSION: Phenolic and flavonoid compounds had great contribution on antioxidant activities by DPPH and CUPRAC. The two methods exposed linear results. Ethanol fruits extract of green honey deli water apple contained quercetin (0.16%) and kaempferol (0.39%).
A General Method for Comparing Probability Assessors

A probability assessor or forecaster is a person who assigns subjective probabilities to events which will eventually occur or not occur. In this paper a general method for comparing forecasters after a finite number of trials is introduced. The general method is proven to include calculating all proper scoring rules as special cases. It also includes comparison of forecasters in all simple two-decision problems as special cases. The relationship between the general method and calibration is also explored. The general method is also translated into a method for deciding who will give better forecasts in the future
On stability and hyperbolicity for polynomial automorphisms of C^2

Let $(f_\lambda)_{\lambda\in \Lambda}$ be a holomorphic family of polynomial automorphisms of $\mathbb{C}^2$. Following previous work of Dujardin and Lyubich, we say that such a family is weakly stable if saddle periodic orbits do not bifurcate. It is an open question whether this property is equivalent to structural stability on the Julia set $J^*$ (that is, the closure of the set of saddle periodic points). In this paper we introduce a notion of regular point for a polynomial automorphism, inspired by Pesin theory, and prove that in a weakly stable family, the set of regular points moves holomorphically. It follows that a weakly stable family is probabilistically structurally stable, in a very strong sense. Another consequence of these techniques is that weak stability preserves uniform hyperbolicity on $J^*$.
MU Face Emotion - Building a Large Dataset for Emotional Facial Expression in Psychological Domain

Currently, several well-known facial datasets have been proposed and used to train artificial intelligence models for facial expression interpretation. However, since each dataset varies in terms of ethnicity and facial expression characteristics, using the currently available dataset does not yield satisfactory results in predicting the emotional expressions of Thai people. As a result, the research team has developed a dataset on the facial expressions of Thai people, which may be used by academics to study and improve-facial expression analysis research. There were two different kinds of datasets created by the research team: audio datasets and image datasets. The research team created two kinds of datasets: audio datasets and image datasets, each of which includes five classes: positive-active (happy), positive-deactivate (relaxed), neutral, negative-active (anger, stress), and negative-deactivate (sad). This dataset was created using data from 24 volunteers who were analyzed for their emotional expression by a group of psychologists from Mahidol University using standardized procedures. The research team calls this information MU-Corpus.
Disenfranchising young people from customary land access; a case of commercialised cashew production in the Brong Ahafo Region of Ghana

Abstract This paper presents a political ecology analysis of intergenerational land dynamics in cashew-producing areas of Ghana’s Brong Ahafo Region. In particular, the paper explores how the growing commercialisation of cashew production for export is driving generational “land grabbing” by older generations and local elites. To do this, we gathered data through interviews, focus groups and observations. Data were analysed through the thematic approach, a process of integrating similar themes from interviews and focus groups. We demonstrate two things: (1) how expanding cashew production is driving generational “land grabbing” by older generations and local elites; (2) how the customary land value is in deep tension with an emerging neoliberal land value. These emerging trends are causing the ‘disenfranchment’ of young people from access to land for cashew production. To this end, the benefits of cashew production for export are likely to elude young people in the region. Based on our findings, we call for a conscious attempt on the part of government to privilege young people’s access to land as part of land reform strategies and also to invest in cashew processing infrastructure to create opportunities for young people to participate in the downstream stages of commercial cashew expansion.
Dysbiotic oral microbiota contributes to alveolar bone loss associated with obesity in mice

Abstract Periodontal diseases (PD) are inflammatory conditions that affect the teeth supporting tissues. Increased body fat tissues may contribute to activation of the systemic inflammatory response, leading to comorbidities. Some studies have shown that individuals with obesity present higher incidence of PD than eutrophics. Objective To investigate the impact of obesity on periodontal tissues and oral microbiota in mice. Methodology Two obesity mice models were performed, one using 12 weeks of the dietary protocol with a high-fat (HF) diet in C57BL/6 mice and the other using leptin receptor-deficient mice (db/db-/-), which became spontaneously obese. After euthanasia, a DNA-DNA hybridization technique was employed to evaluate the microbiota composition and topical application of chlorhexidine (CHX), an antiseptic, was used to investigate the impact of the oral microbiota on the alveolar bone regarding obesity. Results Increased adipose tissue may induce alveolar bone loss, neutrophil recruitment, and changes in the oral biofilm, similar to that observed in an experimental model of PD. Topical application of CHX impaired bone changes. Conclusion Obesity may induce changes in the oral microbiota and neutrophil recruitment, which are associated with alveolar bone loss.
A Classification of RPL Specific Attacks and Countermeasures in the Internet of Things

Although 6LoWPAN has brought about a revolutionary leap in networking for Low-power Lossy Networks, challenges still exist, including security concerns that are yet to answer. The most common type of attack on 6LoWPANs is the network layer, especially routing attacks, since the very members of a 6LoWPAN network have to carry out packet forwarding for the whole network. According to the initial purpose of IoT, these nodes are expected to be resource-deficient electronic devices with an utterly stochastic time pattern of attachment or detachment from a network. This issue makes preserving their authenticity or identifying their malignity hard, if not impossible. Since 6LoWPAN is a successor and a hybrid of previously developed wireless technologies, it is inherently prone to cyber-attacks shared with its predecessors, especially Wireless Sensor Networks (WSNs) and WPANs. On the other hand, multiple attacks have been uniquely developed for 6LoWPANs due to the unique design of the network layer protocol of 6LoWPANs known as RPL. While there exist publications about attacks on 6LoWPANs, a comprehensive survey exclusively on RPL-specific attacks is felt missing to bold the discrimination between the RPL-specific and non-specific attacks. Hence, the urge behind this paper is to gather all known attacks unique to RPL in a single volume.
An Intelligent Automatic Number Plate Recognition System Based on Computer Vision and Edge Computing

The current traffic monitoring system accumulates a large amount of data and apply algorithms to process the received photo and video images through cameras. These data are used to regulate traffic flows, recognize number plate and record traffic collisions. The collected data are traditionally sent to data centers for processing, analyzing, and then sent to the operator. Thus, a large amount of incoming data to the data center and to the traffic monitoring center reduces the network bandwidth and has a negative impact on the speed of decision-making by the operator. To solve this problem, we proposed to use the edge computing paradigm by placing edge nodes in the near vicinity of the cameras and conducting data preprocessing on edge devices. This paper considers the Raspberry Pi as an edge device, as well as computer vision algorithms for pre-processing data at the edge device and the process of transferring data to the data center with the following prompt decision-making by the operator. As a result of usage the edge computing paradigm helps to optimize network traffic and offload the computing power of the data center.
A Novel Revocable Lightweight Authentication Scheme for Resource-Constrained Devices in Cyber–Physical Power Systems

The existing identity security schemes (e.g., based on bilinear pairing) have high computational complexity and large bytes of variables, which results in high computation and communication costs. It is difficult to apply the schemes to resource-constrained (i.e., computation and communication) devices. Moreover, most of these schemes adopt a fixed cycle key update strategy compromising the security of authentication schemes or dynamic (real-time) key update strategy with high computational cost. To solve these issues, this article explores a novel revocable lightweight authentication scheme for resource-constrained devices in cyber–physical power systems (CPPSs). First, a lightweight authentication scheme combined elliptic-curve cryptography (ECC) and certificateless cryptography (CLC) is proposed to negotiate a secure session key, which can achieve mutual authentication with low computation and communication costs. Second, aiming at security problem caused by key leakage, a real-time key update strategy with low computational cost is designed to improve the security of identity authentication. Third, according to a hardness assumption of the elliptic-curve discrete logarithm problem (ECDLP), theoretical analysis rigorously proves that the proposed authentication scheme ensures the security with respect to existential unforgeability against adaptively chosen message attacks (EUF-CMAs). Finally, experimental results confirm the feasibility and effectiveness of the proposed authentication scheme.
Framing, agency, and optimistic bias: message design considerations for the opioid crisis

ABSTRACT While vastly overshadowed by the COVID-19 pandemic, America’s deadly opioid crisis worsened dramatically in recent years. Despite the deadliness of these drugs, the lifesaving medication Narcan (a naloxone product) has saved more than 93.5% of potential victims from an overdose death. However, several factors have contributed to a lack of uptake of the medication. The current study explored message-design components for persuading individuals to 1) seek more information regarding Narcan 2) accept a coupon code for Narcan, and 3) purchase the Narcan nasal spray. Guided by the Extended Parallel Process Model, this study implemented strategic message design to see if heightened perceptions of threat (i.e. severity and susceptibility) and efficacy (self, response, and system efficacy) promote behaviour change to either seek information about or purchase Narcan. We employed three message framing techniques, including gain/loss-frame, labelling and stigmatisation through language, and linguistic assignment of agency. Based on an experimental design with 304 participants and eight message conditions, the study revealed the following: high perceptions of susceptibility and system-efficacy predicted the acceptance of a coupon code for Narcan; high perceptions of severity, susceptibility, and system-efficacy predicted information-seeking behaviour; finally, susceptibility and response-efficacy predicted an intent to own Narcan in the future.
Charged Pion Condensation Phenomenon of Dense Baryonic Matter Induced by Finite Volume: the NJL 2 Model Consideration

The properties of two-flavored massless Nambu–Jona-Lasinio (NJL) model in (1+1)-dimensional R1 × S1 space–time with compactified space coordinate are investigated in the presence of isospin and quark number chemical potentials μI, μ. The consideration is performed in the large Nc limit, where Nc is the number of colored quarks. It is shown that at L = ∞ (L is the length of the circumference S1) the charged pion condensation (PC) phase with zero quark number density is realized at arbitrary nonzero μI and for rather small values of μ. However, at arbitrary finite values of L the phase portrait of the model contains the charged PC phase with nonzero quark number density (in the case of periodic boundary conditions for quark fields). Hence, finite sizes of the system can serve as a factor promoting the appearance of the charged PC phase in quark matter with nonzero baryon densities. In contrast, the phase with chiral symmetry breaking may exist only at rather large values of L.
Dewatering and structural analysis of foam-formed, lightweight fibrous materials

This work studied the effect of the dewatering conditions on the behavior of fiber foams during dewatering and on the final structure of the formed, thick, lightweight lignocellulosic materials. The vacuum level, fiber type, consistency, and basis weight of the fiber foam were all varied. During dewatering, the time evolution of the thickness of the fiber foam in the mold was studied, and the dryness of the fiber foam immediately after dewatering was measured. The density and pore size profiles of the final dry materials was measured using X-ray microtomography (µCT).
Unsupervised Learning Composite Network to Reduce Training Cost of Deep Learning Model for Colorectal Cancer Diagnosis

Deep learning facilitates complex medical data analysis and is increasingly being explored in colorectal cancer diagnostics. However, the training cost of the deep learning model limits its real-world medical utility. In this study, we present a composite network that combines deep learning and unsupervised K-means clustering algorithm (RK-net) for automatic processing of medical images. RK-net was more efficient in image refinement compared with manual screening and annotation. The training of a deep learning model for colorectal cancer diagnosis was accelerated by two times with utilization of RK-net-processed images. Better performance was observed in training loss and accuracy achievement as well. RK-net could be useful to refine medical images of the ever-expanding quantity and assist in subsequent construction of the artificial intelligence model.
(Cr1−xAlx)N Coating Deposition by Short-Pulse High-Power Dual Magnetron Sputtering

The paper deals with the (Cr1−xAlx)N coating containing 17 to 54 % Al which is deposited on AISI 430 stainless steel stationary substrates by short-pulse high-power dual magnetron sputtering of Al and Cr targets. The Al/Cr ratio in the coating depends on the substrate position relative to magnetrons. It is shown that the higher Al content in the (Cr1−xAlx)N coating improves its hardness from 17 to 28 GPa. Regardless of the Al content, the (Cr1−xAlx)N coating manifests a low wear rate, namely (4.1–7.8) × 10−9 and (3.9–5.3) × 10−7 mm3N−1m−1 in using metallic (100Cr6) and ceramic (Al2O3) counter bodies, respectively. In addition, this coating possesses the friction coefficient 0.4–0.7 and adhesive strength quality HF1 and HF2 indicating good interfacial adhesion according to the Daimler-Benz Rockwell-C adhesion test.
A Practical System for 3-D Hand Pose Tracking Using EMG Wearables With Applications to Prosthetics and User Interfaces

Ubiquitous finger motion tracking enables a number of exciting applications in augmented reality, sports analytics, rehabilitation-healthcare, haptics, etc. This article presents NeuroPose, a system that shows the feasibility of 3-D finger motion tracking using a platform of wearable electromyography (EMG) sensors. EMG sensors can sense electrical potential from muscles due to finger activation, thus offering rich information for fine-grained finger motion sensing. However, converting the sensor information to 3-D finger poses is non trivial since signals from multiple fingers superimpose at the sensor in complex patterns. Toward solving this problem, NeuroPose fuses information from anatomical constraints of finger motion with machine learning architectures on recurrent neural networks (RNNs), encoder–decoder networks, and ResNets to extract 3-D finger motion from noisy EMG data. The generated motion pattern is temporally smooth as well as anatomically consistent. Furthermore, a transfer learning algorithm is leveraged to adapt a pretrained model on one user to a new user with minimal training overhead. A systematic study with 12 users demonstrates a median error of 6.24° and a 90%-ile error of 18.33° in tracking 3-D finger joint angles. The accuracy is robust to natural variation in sensor mounting positions as well as changes in wrist positions of the user. In addition, this article validates the feasibility of mirrored bilateral training approach with applications in prosthetic devices. Finally, NeuroPose is comprehensively evaluated on both low-end and recent smartphones with a processing latency of 0.019 s and low energy overhead.
Lane Information Extraction for High Definition Maps Using Crowdsourced Data

Lane information plays an important role in high-definition (HD) maps because it provides invaluable road information for autonomous vehicles. The most widely used lane extraction method for HD maps is based on mobile mapping systems, and it is prohibitively costly and time-consuming. In this study, we propose a novel approach for lane information extraction based on crowdsourcing vehicles equipped with monocular cameras and global navigation satellite system devices for recording road images and position data. First, we propose a lane mask propagation network to detect the lane markings in images, which are then projected from a perspective space into a three-dimensional space in accordance with the position data. Second, we propose a data management method to store lane information in the cloud data center. An improved density-based spatial clustering of applications with noise clustering algorithm and a gradual fitting algorithm are used to remove the outliers and improve the lane data accuracy. The proposed method is quantitatively evaluated against a real-world HD map produced by a mobile mapping vehicle. The experimental results show that more than 80% of the extracted lane markings meet the accuracy requirements of HD maps. In conclusion, our method can be used as a low-cost and efficient approach for updating the lane information in HD maps for autonomous vehicles.
The Mitochondrial Alternative Oxidase in Ustilago maydis Is Not Involved in Response to Oxidative Stress Induced by Paraquat

It has been shown that the alternative oxidase in mitochondria of fungi and plants has important functions in the response against stress conditions, although their role in some organisms is still unknown. This is the case of Ustilago maydis. There is no evidence of the participation of the U. maydis Aox1 in stressful conditions such as desiccation, high or low temperature, and low pH, among others. Therefore, in this work, we studied the role of the U. maydis Aox1 in cells exposed to oxidative stress induced by methyl viologen (paraquat). To gain insights into the role of this enzyme, we took advantage of four strains: the FB2 wild-type, a strain without the alternative oxidase (FB2aox1Δ), other with the Aox1 fused to the Gfp under the control of the original promoter (FB2aox1-Gfp), and one expressing constitutively de Aox1-Gfp (FB2Potef:aox1-Gfp). Cells were incubated for various times in the presence of 1 mM paraquat and growth, replicative capacities, mitochondrial respiratory activity, Aox1 capacity, and the activities of several antioxidant enzymes (catalase, glutathione peroxidase, glutathione reductase, and superoxide dismutase) were assayed. The results show that (1) the response of U. maydis against oxidative stress was the same in the presence or absence of the Aox1; (2) the activities of the antioxidant enzymes remained constant despite the oxidative stress; and (3) there was a decrease in the GSH/GSSG ratio in U. maydis cells incubated with paraquat.