Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of multi-layered QR codes utilizing partitions of positive integers

Multi-layered QR (MLQR) codes are created by superimposing many black and white QR codes, all of which are assigned their white areas with the colors in RGB color space. These colors must be different enough to enable distinguishing each layer of a MLQR code. This makes a MLQR code be able to hold more data than a common QR code. In this work, the procedures for generating and un-layering MLQR codes were proposed and the according graphical user interfaces (GUIs) were created with MATLAB. They use the property of a partition of the number 255, constructed by the geometric sequence { 2n−1 } n∈N, to compute the collection of suitable colors for assigning to black and white QR codes in the generating process. Our developed procedures can promote better intercommunication between human and computers, therefore ensure easier computer programming and being more flexible in the number of layers of created MLQR codes. We found that the developed GUIs could work accurately up to 15 layers because more QR code layers require the use of more colors, which diminish an ability to clearly distinguish the color of each QR code layer.
Additional File 2 for Robust and Efficient Parameter Estimation in Dynamic Models of Biological Systems Methods for tuning regularization

Choosing a method to tune regularization is non-trivial. Bauer and Lukas[1] compared 17 regularization parameter choice methods for a large set of linear least squares problems. Apart from the numerical case studies, they also provided a unified framework to discuss the numerical aspects of each method, and the performance of the regularization methods from the estimated parameters point of view. We can see that most of the methods work very well in terms of achieving a small mean square error in the estimated parameters. However, small parameter estimation error do not imply small prediction errors. Most of the regularization tuning methods can be used together with nonlinear least squares (NLS) methods, such as e.g. the Landweber algorithm, the iteratively regularized Gauss Newton method or conjugate gradient method [2]. These optimization methods iteratively update the parameter estimates by a suitable step for which the residual vector or the objective function (depending on the method) is linearized in each step and the regularization is applied to the steps. Our approach is different, since we apply the regularization directly to the parameter vector instead of the updating steps, which allow us to use the regularization in both the global and the local optimization phases. In the following section we shortly summarize the regularization tuning methods considered and their computational details, which we utilized for the Tikhonov regularization of the hybrid optimization algorithm presented in the main text. In the following sections we also report the results of the regularization tuning methods for each case study. For each problem, the regularization parameter selected by the regularization tuning method is compared against the bias-variance trade-off curves (both for the bias-variance in the estimated parameters and in the estimated predictions). Note that the performance of a tuning method is evaluated based on the distance of the selected regularization parameter from the location of the minimum of the bias-variance trade-off curves.
Religious and political intersections: the instrumentalisation of Christianity during Zimbabwe’s 2018 presidential elections

ABSTRACT This article discusses the critical intersection of Christianity with Zimbabwean politics during the 2018 harmonised elections. Christianity and politics play an important role in organising or polarising society. Major problems arise when the church becomes more “political” than spiritual or becomes silent on political matters affecting society. Religion has been used for various purposes in Zimbabwean politics, such as holding on to power, contesting power, rebuking leaders and silencing opponents. In the current research, my interest lies in two specific aspects; how, firstly, the ruling Zimbabwe African National Union-Patriotic Front (ZANU-PF) leader, Emmerson Mnangagwa, and, secondly, the opposition Movement for Democratic Change-Alliance (MDC-A’s) Nelson Chamisa evoked Christianity in their national electoral campaign through rallies and posts on social media, before the 2018 harmonised elections and during the disputation of the results. The article concludes that Chamisa and Mnangagwa instrumentalised Christianity differently as a political tool.
PIN Inference Attack: A Threat to Mobile Security and Smartphone-Controlled Robots

The proliferation of smartphones equipped with various sensors created a large user base, which includes robots (smartphone controlled) as well. The high processor enabled smartphones are used as software robots to track hour-to-hour activities of users using on-board motion sensors. The magnetometer, accelerometer, and gyroscope are non-permission based motion sensors. The logs of these sensors create discriminative patterns to identify users’ movements. This leverages an adversary to cause privacy threats using these non-permission based sensors without user consent. Recent works also highlighted the privacy threats due to the motion sensors in smartphones. Therefore, in this paper, we present a potential misuse of technology where smartphones can be hacked by PIN Inference attack endangering the mobile security. Once the smartphone is compromised, it may lead to various repercussions. We discuss one such case where after PIN is inferred the adversary incorrectly uses our robot made for corridor detection. With this example, we show the severity of the PIN-Inference attack as nowadays many user activities are governed by robots. We perform experiments to collect motion sensors’ data and infer 4-digit PIN of a smartphone. Our strategy is to detect every key pressed one by one constituting a 4-digit PIN. Our inference results are promising and prove that an adversary can make use of sensors’ data to infiltrate user’s sensitive information from smartphones. Our proposed model infers 84% of the PINs correctly within 40 attempts when tested on 50 PINs. Given real Android devices with different users, we can identify the PIN of smartphones by training our machine learning based model. We also compare our approach with existing state-of-the-art approaches to show the efficacy of our attack model.
Morpho-molecular characterization of causative agents of wilting, leaf spot, fruit blight and stem canker of okra (Abelmoschus esculentus L.)

Abstract This study aimed at identification and characterisation of the wilting, leaf spot, stem canker and fruit-blight diseases of okra. Pathogen infected plant samples were sterilised with 2% sodium hychlorite solution for 20 mins and then cultured at 28 °C for 15 days followed by microscopic examination. Combined microscopic, morphological and cultural characteristics analyses identified the four okra fungal isolates (OFI) such as OFI-1, OFI-2, OFI-3 and OFI-4 as Fusarium oxysporum, Curvularia lunata, Fusarium chlamydosporum and Choanephora cucurbitarum, respectively. The isolates OFI-1, OFI-2, OFI-4 showed highest radial growth rates at 25 °C, pH 5 and 20% lactose containing media while it was sucrose for OFI-3. BLASTN search using the sequence of ITS regions revealed that OFI-1, OFI-2, OFI-3 and OFI-4 isolates had 98, 100, 97 and 100% homology with F. oxysporum, C. lunata, F. chlamydosporum and C. cucurbitarum, respectively. Pathogenicity tests were also confirmed by reproducing the disease symptoms in okra plants.
Implementation of a Distributed Home Automation Scheme with Custom Hardware Nodes Using ZigBee and MQTT Protocols

Providing safety, security, operational convenience and energy savings are some of the vital goals of a home automation system. A single unified point of interaction for the user is also an important consideration. Each feature requires a different sensor, powering scheme and mounting arrangement. To address each requirement, custom node development is to be prepared with all nodes being part of a personal area network for data transfer. A central node with Internet connectivity can push data to the cloud and the user can be provided access to data on a mobile app. This paper presents the practical implementation of such a distributed home automation scheme with custom-designed microcontroller-based ZigBee enabled hardware nodes for liquid petroleum gas leak detection, window open detection, lights switching control based on occupancy and intrusion detection. Messages are triggered by events and are not periodic to avoid traffic congestion. A central node built around a Raspberry Pi with a ZigBee dongle will serve as a data aggregator which sends messages to our own MQTT (Message Queuing Telemetry Transport) broker. An android mobile app will work as an MQTT client, helps the user to connect the MQTT broker, subscribe to the topics published and makes alerts to the user as soon as an event occurs. The mobile app will also enable the user to switch on lights and other appliances through command messages sent to the MQTT broker and subscribed to Raspberry Pi.
Decoupled EPS Control Utilizing Magnetizing Current to Achieve Full Load Range ZVS for Dual Active Bridge Converters

A decoupled extended phase shift control is proposed to decrease the control complexity and achieve full load range zero voltage switching (ZVS) for dual active bridge (DAB) dc–dc converters. In the proposed solution, full load range ZVS is achieved by adding an extra small fixed duty cycle and utilizing the magnetizing current. In addition, the two control variables are decoupled, since the control of the duty cycle is only determined by the voltage conversion ratio and is independent of the phase shift angle, which avoids the detection of operation mode and switching of control laws. The ZVS model considering junction capacitors and magnetizing inductance, ZVS region under full load range, and derivation of control law are analyzed in detail. Finally, the effectiveness of the proposed solution is experimentally verified on a 500-W, 250kHz GaN-based prototype.
The Non‐Negligible Effect of Viscosity Diffusion on the Geodynamo Process

Exploring geodynamo's scaling laws is of great importance when a tremendous gap still lies between realistic physics and estimated model parameters. Existing scaling laws need to be tested by numerical simulations. To boost these, taking the outer core viscosity ν , we studied its impacts on weak and strong field geodynamo outputs by varying ν in two orders of magnitudes. In the weak field mode, the fluid velocity u varies with ν by a scaling law of u∼ν0. 52 . While in the strong field mode, u varies very slowly by a scaling law of u∼ν0. 10 . The magnetic field B does not change much with ν when the driving force is not too strong ( Ra=12,000 ) but decreases with ν by a scaling law of B∼ν−0.20 when geodynamo operates in a very vigorous mode ( Ra=50,000 ). The reason that u increases with ν is essential that increasing ν breaks the Taylor‐Proudman constraint and drops the critical Rayleigh number, but this kind of increase of u does not give a stronger B . Furthermore, we conducted a local force balance analysis and demonstrated that the balance shifts under different ν . In a quasi‐MAC regime, the Lorentz force instead of the inertial force enters into the first‐order agostrophic force balance, though the viscous force still plays a role. Comparing with other scaling laws previous wisdom holds, we propose that the effect of viscosity diffusion is non‐negligible for both existing weak and strong dynamo regimes. Still, appropriate assumptions can be made to take this variation into account.
Representing the moraic nasal in Japanese: evidence from Tōkyō, Ōsaka and Kagoshima

This article reconsiders the nature and representation of the moraic nasal <N> in Japanese dialects, which is largely assumed to be a consonantal mora (Ito 1987, Vance 2008, Labrune 2008) or a variable segment (Yoshida S. 1996, 2003; Yoshida Y. 1999). I examine phonological processes and phonetic descriptions of the Tōkyō, Ōsaka and Kagoshima varieties of Japanese and show that previous representations do not capture all of the facts. I propose that N is best represented variously as a nasal consonant, a syllabic nasal or a nasal vowel depending on the dialect. I frame this account within the theory of Strict CV (Lowenstamm 1996) and I present new representations for N, taking into account segmental and prosodic behaviour of this segment. The overarching contribution is an analysis where the tonal status of N in Japanese dialects is directly derived from the status of nuclear positions that N is associated to or adjacent to, without reference to feature sensitive rules. CONNOR YOUNGBERG Representing the moraic nasal in Japanese: evidence from Tōkyō, Ōsaka and Kagoshima CORRESPONDING AUTHOR: Connor Youngberg Laboratoire de Linguistique de Nantes (UMR-6310)/Université de Nantes, FR Connor.Youngberg@univnantes.fr
Multilevel space‐time multiplicative Schwarz preconditioner for parabolic equations

Space‐time methods are able to solve time‐dependent problems faster by exploiting the full power of high‐performance computer. In this article, a multilevel space‐time multiplicative Schwarz method is presented for solving parabolic equations in parallel on both spatial and temporal directions. In the implementation, the proposed Schwarz method is treated as preconditioner for GMRES, that is, a coupled system arising from the discretization of the parabolic equation is solved by using a multiplicative Schwarz preconditioned GMRES algorithm. We develop an optimal convergence theory to show that the convergence rate is bounded and independent of the spatial mesh sizes, the time step size, the number of subdomains, the number of levels, and the window size. Some numerical results obtained on a parallel computer with thousands of processors are presented to confirm the theory in terms of optimality and scalability. Moreover, numerical comparisons with traditional time‐stepping algorithms show that the proposed space‐time method earns lots of benefits when the number of processor cores is large.
Predator-based selection and the impact of edge sympatry on components of coral snake mimicry

Mimicry is a vivid example of how predator-driven selection can impact phenotypic diversity, which itself can be influenced by the presence (sympatry) or absence (allopatry) of a dangerous model. However, the impact of sympatry and allopatry on predation on mimicry systems at fine spatial scales (e.g., edge sympatry, allopatry) is not well understood. We studied mimicry in a montane tropical site in Honduras with an abrupt elevational gradient where coral snakes and mimics exist in close sympatry and allopatry. Specifically, we used clay replicas to test the impact of edge sympatry on (1) overall attack rates, (2) the fitness benefit of mimetic coloration, and (3) predation on specific mimetic signal components. Unlike previous research, we found that mimetic phenotypes received significantly more attacks than cryptic replicas in edge sympatry, suggesting that mimetic phenotypes might not confer a fitness benefit in areas of edge sympatry. Additionally, we documented temporal variation in predator-based selection, as the impacts of allopatry on predatory attacks varied among years. Our results imply that the effect of sympatry and allopatry on predator-based selection in mimicry systems may be more complex than previously thought for species-rich assemblies of coral snakes and their mimics in the montane tropics.
Cognitive Deficits and Alcohol Dependence Syndrome– A Paradigm Relationship

Background– Chronic alcohol use causes not only physical consequences but causes cognitive deficits also. 50 and 80% of the Alcohol dependent syndrome patients present with cognitive deficits. These cognitive deficits will significantly contribute to poor functional outcomes which lead to reduced health related quality of life. Objectives- 1. To assess Cognitive deficits in Alcohol Dependent syndrome (ADS). 2.To find the relationship between early onset of alcohol use, duration of Alcohol use and large quantity of alcohol use with Cognitive deficit pattern. Method- A cross sectional study was done on 38 patients with ADS, aged 18- 45 years, education ≥7th std, with no major psychiatric or medical co- morbidities. AUDIT scale was administered to look for dependence pattern, CIWA scale was applied to look for withdrawal symptoms. MoCA scale was applied to screen for cognitive impairment in patient with MMSE score (25 and above). In subjects with cognitive impairment on MoCA scale (25 and below), neuropsychological assessment was done using neuropsychological battery of test from NIMHANS Neuropsych battery standardised on Indian Population. Results-There was impairment in the Cognitive domains as follows, speed of processing (BACS – 100%), attention (DF- 97%) working memory (DF-97%, DB-100%, LNS – 84%), visual memory (100%), visuo-spatial memory (78%), executive functions (CT2 -92%), reasoning and problem solving (maze- 81%) in majority and a significant relation between early onset of alcohol use, duration of Alcohol use. Conclusions- There is a significant impairment in the areas of speed of processing, attention, executive functions, reasoning and problem-solving domains. Significant association between Age of onset of ADS (Early onset) with Executive functions. Attention domain was found to be associated with longer duration of alcohol intake, whereas working memory deficits was associated with large quantity of alcohol intake.
Fast Multi-View Clustering via Prototype Graph

Multi-view clustering attracts considerable attention due to its effectiveness in unsupervised learning. However, previous multi-view spectral clustering methods include two separated steps: 1) Obtaining a spectral embedding; 2) Performing classical clustering methods. Although these methods have achieved promising performance, there is still some limitations. First, in computing spectral embedding, multi-view spectral clustering approaches exist high computational complexity since they usually need eigenvalue decomposition on laplacian matrix <inline-formula><tex-math notation="LaTeX">$L$</tex-math><alternatives><mml:math><mml:mi>L</mml:mi></mml:math><inline-graphic xlink:href="shi-ieq1-3078728.gif"/></alternatives></inline-formula>; Second, in constructing similarity matrices, previous methods need to compute similarity between any two samples; Third, the two-stage approach only can obtain the sub-optimal solution; Fourth, treating equally all views is unreasonable. To address these issues, we propose a Fast Multi-view Clustering via Prototype Graph (FMVPG) method. Specifically, the prototype graph is first constructed, and then simultaneously perform spectral embedding to obtain the real matrix and spectral rotation to get the indicator matrix. In addition, the alternative optimization strategy is used to solve the proposed model. Further, we conduct extensive experiments to evaluate the proposed FMVPG approach. These experimental results show the comparable or even better clustering performance than the state-of-the-art approaches.
Approximating triangular meshes by implicit, multi-sided surfaces

The I-patch is a multi-sided surface representation, defined as a combination of implicit ribbon and bounding surfaces, whose pairwise intersections determine the natural boundaries of the patch. Our goal is to show how a collection of smoothly connected I-patches can be used to approximate triangular meshes. We start from a coarse, user-defined vertex graph which specifies an initial subdivision of the surface. Based on this, we create ribbons that tightly fit the mesh along its edges in both positional and tangential sense, then we optimize the free parameters of the patch to better approximate the interior. If the surfaces are not sufficiently accurate, the network needs to be refined; here we exploit that the I-patch construction naturally supports T-nodes. We also describe a normalization method that nicely approximates the Euclidean distance field, and can be efficiently evaluated. The capabilities and limitations of the approach are analyzed through several examples.
Signatures of the Carrier Envelope Phase in Nonlinear Thomson Scattering

High-energy radiation can be generated by colliding a relativistic electron bunch with a high-intensity laser pulse—a process known as Thomson scattering. In the nonlinear regime the emitted radiation contains harmonics. For a laser pulse whose length is comparable to its wavelength, the carrier envelope phase changes the behavior of the motion of the electron and therefore the radiation spectrum. Here we show theoretically and numerically the dependency of the spectrum on the intensity of the laser and the carrier envelope phase. Additionally, we also discuss what experimental parameters are required to measure the effects for a beamed pulse.
Lagoa do Quari (São Raimundo Nonato, Piauí): Palaeoenvironment and wetland archaeology in Northeastern Brazil

Northeastern Brazil has thousands of wetland fossiliferous deposits with megafauna and, in some cases, associated lithic artifacts. The timing of the arrival of humans in South America and the extinction of megafauna is still debated and these sites contribute both to this discussion and to the reconstruction of the Late Pleistocene and Holocene paleoenvironment. Lagoa do Quari, 40 km south of São Raimundo Nonato, Piauí state, is a marsh deposit in the present semiarid caatinga environment, excavated by an interdisciplinary team in 2002–2003. This paper presents the archaeological, palaeontological, geological, chronological, stratigraphical and palynological results and their implications for the Quaternary of northeastern Brazil. The site has a rich megafaunal bonebed at the bottom, dominated by Eremotherium giant sloth remains with poor biodiversity, and a sandy‐silty deposit at the top; two 14C dates constrain this latter layer to 9,944–9,557 and 6,308–6,177 cal. years BP and the associated rich lithic industry of quartz and chert shows a technical continuity throughout the Holocene in the region. Palynology describes an open landscape with periodic wet phases, which could explain the richness of the archaeological occurrences in Holocenic Brazilian prehistory. This study offers a model of interdisciplinary enquiry into the paleoenvironment and prehistory of lowland South America.
α-Fe2O3/NiOOH: An Effective Heterostructure for Photoelectrochemical Water Oxidation

The study of the semiconductor/electrocatalyst interface in electrodes for photoelectrochemical water splitting is of paramount importance to obtain enhanced solar-to-fuel efficiency. Here, we take into consideration the multiple effects that a thin layer of photodeposited amorphous Ni-oxyhydroxide (NiOOH) induces on hematite (α-Fe2O3) photoanodes. The reduction of overpotential produced a photocurrent onset potential advance of 150 mV and an increase of photocurrent of about 50% at 1.23 V vs RHE. To give an interpretation to these phenomena, we carried out deep electrochemical investigations by cyclic voltammetry and electrochemical impedance spectroscopy. The effective charge injection into the electrolyte due to the reduction of the charge transfer resistance at the electrode/electrolyte interface was observed and increased along with the amount of deposited NiOOH. The benefits of NiOOH deposition are ascribable to its ability to scavenge holes from hematite surface traps. This effect is mitigated at a.