Miracle-dz/UniFAR-FTUs huggingface dataset:
Seed Treatment with Illite Enhanced Yield and Nutritional Value of Soybean Sprouts

Soybean sprouts, a nutritional food product, can contribute to food security because they can be grown within a week and do not require sophisticated technology. The yield and quality of soybean sprouts are influenced by various factors, including seed priming and growing conditions. The objective of this study was to investigate the effects of seed soaking in different concentrations of illite, a clay mineral, on the yield and quality of soybean sprouts. Soybean seeds soaked in five concentrations (0.5%, 1%, 3%, 5%, and 10%, w/v) of illite or tap water for 8 h were named IP-0.5, IP-1, IP3, IP-5, IP-10, and control, respectively. The highest sprout yield was found in IP-3, followed by IP-1, and IP-5, which had 11.1%, 8.8%, and 7.4% increments, respectively, compared to the control. The content of vitamin C, mineral element, isoflavone, total polyphenol, and total flavonoid was higher in many of the illite-treated soybean sprouts than in the control. The overall results indicated that pre-soaking soybean seeds in lower concentrations (0.5−3%, w/v) of illite could be helpful to enhance the yield and nutritional value of soybean sprouts in an easy and inexpensive way.
Hands-Free Authentication for Virtual Assistants with Trusted IoT Device and Machine Learning

Virtual assistants, deployed on smartphone and smart speaker devices, enable hands-free financial transactions by voice commands. Even though these voice transactions are frictionless for end users, they are susceptible to typical attacks to authentication protocols (e.g., replay). Using traditional knowledge-based or possession-based authentication with additional invasive interactions raises users concerns regarding security and usefulness. State-of-the-art schemes for trusted devices with physical unclonable functions (PUF) have complex enrollment processes. We propose a scheme based on a challenge response protocol with a trusted Internet of Things (IoT) autonomous device for hands-free scenarios (i.e., with no additional user interaction), integrated with smart home behavior for continuous authentication. The protocol was validated with automatic formal security analysis. A proof of concept with websockets presented an average response time of 383 ms for mutual authentication using a 6-message protocol with a simple enrollment process. We performed hands-free activity recognition of a specific user, based on smart home testbed data from a 2-month period, obtaining an accuracy of 97% and a recall of 81%. Given the data minimization privacy principle, we could reduce the total number of smart home events time series from 7 to 5. When compared with existing invasive solutions, our non-invasive mechanism contributes to the efforts to enhance the usability of financial institutions’ virtual assistants, while maintaining security and privacy.
A parvocellular-magnocellular functional gradient in human visual cortex

The magnocellular and parvocellular systems are major visual recognition pathways, with distinct histological and physiological properties. Despite their critical role, there is limited evidence on the specific contributions these visual pathways make to visual recognition in general and to word reading in particular. Using a multimodal functional MRI approach and individual-subject analyses, here we investigate the involvement of visual cortex regions in the recognition of magnocellular- and parvocellular-biased words and images. Our results reveal a functional gradient in the activation profile of both left and right visual cortex: posterior regions are more strongly recruited for processing parvocellular-biased, while anterior regions are more involved in processing magnocellular-biased stimuli. Furthermore, functional connectivity analyses show clustering in the strength of functional coupling among visual cortex regions as a function of the distance between regions, with greater coupling within and less coupling across posterior and anterior regions. Finally, we found minimal differences in lateralization for word and image recognition in these visual cortical regions. These results were replicated in a retest session with a subset of participants. Our findings underscore a functional division of labor in the visual cortex as a function determined by a parvocellular or magnocellular bias in properties of the stimuli and further reveal that in this context the visual cortex is not particularly biased towards words or images.
Proactive Eavesdropping With Jamming Power Allocation in Training-Based Suspicious Communications

This letter studies proactive eavesdropping with one legitimate monitor (E) in the classical single-hop suspicious communication. Specifically, unlike all previous works that ignored the suspicious channel training phase and just considered the jamming power optimization of E in the suspicious data transmission phase to facilitate eavesdropping, this letter advances the research by comprehensively investigating the jamming power allocation of E in both phases, with the purpose of maximizing its eavesdropping success probability. Under this setup, we first derive an exact expression of the objective and reveal the existence of a fundamental trade-off in deciding the jamming power allocation, for which a simple one-dimensional search is employed to find the optimal solution. To simplify the analysis, we further derive a tight approximation of the objective and then develop a very fast alternating optimization algorithm to find the sub-optimal jamming power allocation. Moreover, we extend our analysis to the case where the channel state information is available at the suspicious transmitter via channel feedback. Simulation results demonstrate the effectiveness of our proposed scheme compared to competitive benchmarks.
Express detection and discrimination of visual objects by primate superior colliculus neurons

Primate superior colliculus (SC) neurons exhibit rich visual feature tuning properties and are implicated in a subcortical network hypothesized to mediate fast threat and/or conspecific detection. However, the mechanisms through which generalized object detection may be mediated by SC neurons remain unclear. Here we explored whether, and how quickly, SC neurons detect and discriminate real-life object stimuli. We presented experimentally-controlled gray-scale images of seven different object categories within the response fields (RF’s) of SC neurons, and we also presented a variety of luminance- and spectral-matched image controls. We found that all of our functionally-identified SC neuron types preferentially detected real-life objects even in their very first stimulus-evoked visual bursts (starting within approximately 50 ms from image onset). Intriguingly, even visually-responsive motor-related neurons exhibited such robust early object detection, and they also preferentially discriminated between object categories in their initial visual bursts. We further identified spatial frequency information in visual images as a critical source for early object detection and discrimination by SC neurons. Our results demonstrate rapid and robust SC processing of visual objects, and they underline how the visual processing capabilities of the primate SC support perception and action.
Fear, Phobia, Anxiety and Depression symptom levels in Rheumatoid arthritis and Ankylosing Spondylitis patients during the COVID-19 outbreak

Abstract Aim: This study aims to investigate the psychological symptom levels associated with COVID-19 in rheumatoid arthritis and ankylosing spondylitis in remission. Methods: A cross-sectional study was conducted between October 1 and December 31, 2020. Two hundred forty-eight patients meeting the criteria were included in the study. Coronavirus-induced fear, phobia, depression, and anxiety symptoms were evaluated. For this purpose, the Fear of COVID-19 Scale (FCV-19S), Covid-19 Phobia Scale (C19P-S), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI) were used. Results: Most of the participants had high levels of fear, anxiety, and depressive symptoms. C19P-S, FCV-19S, BDI, and BAI scores showed significant simultaneous correlations (p<0.05, each other). The scores of the patients using Biological DMARDs (Disease-modifying antirheumatic drugs) were significantly higher (p <0.001). The scores of the healthcare workers were significantly higher (p <0.001). Among those who interrupted their routine outpatient visits, the rate of those who did not catch COVID-19 was higher (74.7%) (p <0.01). Common risk factors for symptoms of fear, anxiety, and depression associated with COVID-19 were concomitant illness and being a healthcare worker. Conclusions: By transferring current recommendations on COVID-19 and chronic diseases to more patients, exaggerated fear caused by both their diseases and the drugs used can be prevented, and the continuation of the treatment can be contributed. In addition, if necessary, consulting the relevant departments for supportive and medical treatments may contribute to the continuation of the treatment and the prevention of the activation of the disease.
Preceding Vehicle Detection Based on Laser and CCD

Considering the complementarities of data obtained by radar and computer vision,a method of preceding vehicle detection using the image and the radar data was proposed.The improved DBSCAN was proposed to process the laser data according to their characteristics.During the vehicle detection,the vehicle hypothesis was generated with the fusion of laser data and image.After vehicle hypothesis formation,then,features were fuzzed and the vehicle detection was realized according to the confidence obtained by fuzzy inference system.The results indicate that the algorithm can detect vehicle without constricts of lane lines and it has good adaptive ability and anti-jamming ability.It can detect the proceeding vehicles accurately.
Simulated in vitro hypoxic conditions from psoriatic arthritis cartilage change plasminogen activating system urokinase and serpine functionality. Reversal of antiapoptotic protection suggests common homeostatic buffering

Introduction Rheumatoid and psoriatic arthritis are both characterised by synovial destruction associated with a higher turnover of the extracellular matrix. In both conditions, inflammatory processes create hypoxic environments which destabilise members of the plasminogen activating system. Aim Comparing the effect of bioactive concentrations of urokinase (uPA) and serpine (PAI-1) on cellular survival of human fibroblast-like-synoviocytes (HFLS) in rich and hypoxic growth media. Material and methods Monocultures of HFLS were exposed to bioactive uPA and PAI-1 concentrations in both media conditions for 24, 48 and 72 h. Cellular survival was evaluated with a cell viability assay by spectrum absorbance of formazan reduced WST-8. Results PAI-1 at 0.1 and 1 μg/ml was found to stimulate cell viability under hypoxic stress at 48 and 72 h of incubation, with the effect increasing from 48 to 72 h. uPA increased cell viability in rich medium at 48 and 72 h of incubation between 5 and 40 ng/l, but was found to reduce viability at 80 ng/l at 24 and 48 h. PAI-1 increased cell viability in the hypoxic stress model, while high concentrations of uPA decreased cell viability in rich medium. Conclusions The alternative modes of function at extreme concentrations provide a novel description of PAI-1 and uPA activity based on their colocalization and mutual buffering capacity, helping to place these molecules more accurately in the context of arthritic synovial deterioration.
Low Complexity Correlation Power Analysis by Combining Power Trace Biasing and Correlation Distribution Techniques

Side channel attack (SCA) is a class of crypt-analytic attacks for security evaluation of cryptographic and embedded microprocessor implementations. Among several SCA approaches, the correlation power analysis (CPA) is an efficient way to recover the secret key of the specific cryptographic algorithms running on the target devices such as embedded microprocessors. However, the evaluation process is time-consuming since a large number of traces are required to overcome the impact of noise. Hence, this paper proposes new methods to reduce the computation time by using Point of Interest (POI) extractor with the power trace biasing technique and the correlation distribution for the low complexity correlation power analysis (CPA). The theoretical explanations are provided and the experiments on different platforms such as ASCAD and RISC-V processor based databases are conducted to justify the proposed techniques. Especially, our experiments are performed with different protected schemes such as masking, hiding and combined hiding-masking techniques. The experimental results indicate that our proposed methods provide reliable results in comparison with the standard CPA. By using only a half of the power traces for taking the POIs, our first proposal not only decreases the execution time approximately by half but also enhances the success rate of the attack. Moreover, the second method based on power trace biasing technique is proposed in order to achieve better results and reduce the number of traces needed for selecting the POIs. With only 28.9% of given power traces needed, our second proposed technique reduces the execution time to only 2.6 times of the standard CPA.
A Tutorial on Multiple Extended Object Tracking

This tutorial introduces state-of-the-art methods for tracking multiple spatially extended objects based on unlabeled noisy point clouds, e.g., from radar or lidar sensors. In the first part, the focus lies on tracking a single extended object, i.e., the objective is to simultaneously estimate the shape and position of a moving object based on spatially distributed noisy detections. Model-based approaches for tracking elliptical and star-convex shaped objects are treated. Furthermore, recent learning-based approaches are discussed, which learn the spatial distribution of detections from real data. The second part considers the track management and data association problem, i.e., the initialization and termination of tracks as well as the association of detections to objects. After an in-depth analysis of the data association problem for extended objects, various data association approaches are discussed. Finally, recent frameworks for multiple extended object tracking are introduced such as the random finite set-based Poisson multi-Bernoulli mixture framework.
Gaya Visual Etalase sebagai Alternatif Media Komunikasi Grafis Pada Bisnis Kuliner Masakan Padang : Studi Reflective Observation RM Padang

Pada area visual, gaya merupakan cara khas yang memungkinkan pengelompokan objek ke dalam kategori terkait. Etalase dalam hal ini merupakan media komunikasi grafis alternatif yang berperan sebagai saluran komunikasi dari produk yang di-display di dalamnya. Bukan hanya fashion, bisnis kuliner pun mulai menggunakan Etalase untuk memajang kuliner utamanya dengan gaya visual yang khas yang membedakan dengan rumah makan lainnya; salah satunya yang menjadi objek dalam penelitian ini adalah Rumah Makan Padang. Mengadaptasi Metode Kolb dalam Kerangka Berpikir Experiential Learning pada pengembangan penelitian di area Psikologi Desain, penelitian ini menggunakan pendekatan Reflective Observation untuk mengidentifikasi gaya visual pada Etalase Rumah Makan Padang dalam jarak tempuh tertentu. Dari hasil penelitian, disimpulkan bahwa Gaya Visual Etalase RM. Padang dapat berfungsi sebagai media komunikasi grafis yang dalam proses perseptual berpotensi mengembangkan style navigations pada bisnis kuliner Padang.
TIDE: Temporally Incremental Disparity Estimation via Pattern Flow in Structured Light System

We introduced Temporally Incremental Disparity Estimation Network (TIDE-Net), a learning-based technique for disparity computation in mono-camera structured light systems. In our hardware setting, a static pattern is projected onto a dynamic scene and captured by a monocular camera. Different from most former disparity estimation methods that operate in a frame-wise manner, our network acquires disparity maps in a temporally incremental way. Specifically, We exploit the deformation of projected patterns (named pattern flow) on captured image sequences, to model the temporal information. Notably, this newly proposed pattern flow formulation reflects the disparity changes along the epipolar line, which is a special form of optical flow. Tailored for pattern flow, the TIDE-Net, a recurrent architecture, is proposed and implemented. For each incoming frame, our model fuses correlation volumes (from current frame) and disparity (from former frame) warped by pattern flow. From fused features, the final stage of TIDE-Net estimates the residual disparity rather than the full disparity, as conducted by many previous methods. Interestingly, this design brings clear empirical advantages in terms of efficiency and generalization ability. Using only synthetic data for training, our extensitve evaluation results (w.r.t. both accuracy and efficienty metrics) show superior performance than several SOTA models on unseen real data. The code will be available on https://github.com/CodePointer/TIDENet soon.
PRIMENA BEZBEDNOSNIH ELEMENATA AZURE PLATFORME U SISTEMIMA ZA ELEKTRONSKA PLAĆANJA

U ovom radu predstavljeni su problemi i izazovi sistema koji se bave eletktronskim plaćanjima. Predstavljen je jedan koncept sistema kroz koji su istra­žene bezbednosne kontrole i zahtevi nekih od regulativa čije implementacije se smatraju obaveznim. Poseban akcenat stavljen je na mehanizme koje pruža i olakšava Microsoft Azure platforma. Istraženo je više servisa koje ova platforma nudi i opisani su prednosti ali i nedostaci istih.
A Technique for Tracking the Global Peak of PV Arrays During Partially Shaded Conditions Using the Detection of Current Source and Voltage Source Regions of I–V Curves

This article proposes a methodto track the global peak (GP) when the photovoltaic (PV) arrays receive uniform or partial irradiance. The proposed method employs the current–voltage (I–V) curve of the PV generator to track the maximum power point. It can distinguish whether the operating voltage is lying in the voltage source region (VSR) or the current source region (CSR) of the I–V curve using current information at different operating points. It also uses the slope of the I–V curve for discriminating CSR and VSR. This helps the algorithm track the movement of the operating point from VSR to CSR, which further helps in avoiding the false tracking of local peaks (LPs) during global maximum power point tracking. After all LPs are tracked, the LP with maximum power is set as a GP.The performance of the presented algorithm is verified using simulation in the MATLAB/Simulink environment and also supported with experimental results using hardware setup.
Effects of Sulfamethazine and Cupric Ion on Treatment of Anaerobically Digested Swine Wastewater with Growing Duckweed

Duckweed (Spirodela polyrrhiza) has the potential to treat anaerobically digested swine wastewater (ADSW), but the effects of antibiotics and heavy metals in ADSW on the treatment performance and mechanism of Spirodela polyrrhiza are not clear. Herein, an experiment was conducted to investigate the effects of sulfamethazine (SMZ) and cupric ion on NH4+-N and total phosphorus (TP) removal from synthetic ADSW. The activity of superoxide dismutase (SOD) and the contents of photosynthetic pigments, vitamin E, and proteins in duckweed were also evaluated. Under the stress of SMZ, duckweed showed excellent removal efficiency of nutrients, and the results of SOD activity and photosynthetic pigments content indicated that duckweed had good tolerance to SMZ. Interestingly, a combined application of SMZ and cupric ion would inhibit the nutrient removal by duckweed, but significantly increased the contents of photosynthetic pigments, proteins, and vitamin E. In addition, the consequence indicated that high value-added protein and vitamin E products could be produced and harvested by cultivating duckweed in ADSW. Furthermore, possible degradation pathways of SMZ in the duckweed system were proposed based on the analysis with LC-MS/MS. This research proposed a novel view for using duckweed system to remove nutrients from ADSW and produce value-added products under the stress of SMZ and cupric ion.
Parametric variation analysis of CUKconverter for constant voltage applications

This paper presents an optimized controller for non-isolated DC-DC CUK converter for constant voltage applications. CUK converter has inverted voltage polarity at the output, however, it operates on the principle of capacitive energy transfer and uses inductors on both sides of the switch to reduce current ripple. MOSFETs are used as a switching device in low power and high frequency switching applications. It may be noted that, as the turn-on and turn-off time of MOSFETs are lower as compared to other switching devices, which reduces the switching losses. High frequency operation of MOSFET reduced size of filters components. These converters are now being used for various applications, such as Switched Mode Power Supply (SMPS) etc. The paper attempts to present parametric variation analysis of buck-boost converters for constant voltage output.
Chloride Channels and Transporters: Roles beyond Classical Cellular Homeostatic pH or Ion Balance in Cancers

Simple Summary Roles of chloride-associated transporters have been raised in various cancers. Although complicated ion movements, crosstalk among channels/transporters through homeostatic electric regulation, difficulties with experimental implementation such as activity measurement of intracellular location were disturbed to verify the precise modulation of channels/transporters, recently defined cancerous function and communication with tumor microenvironment of chloride channels/transporters should be highlighted beyond classical homeostatic ion balance. Chloride-associated transporters as membrane-associated components of chloride movement, regulations of transmembrane member 16A, calcium-activated chloride channel regulators, transmembrane member 206, chloride intracellular channels, voltage-gated chloride channels, cystic fibrosis transmembrane conductance regulator, voltage-dependent anion channel, volume-regulated anion channel, and chloride-bicarbonate exchangers are discussed. Abstract The canonical roles of chloride channels and chloride-associated transporters have been physiologically determined; these roles include the maintenance of membrane potential, pH balance, and volume regulation and subsequent cellular functions such as autophagy and cellular proliferative processes. However, chloride channels/transporters also play other roles, beyond these classical function, in cancerous tissues and under specific conditions. Here, we focused on the chloride channel-associated cancers and present recent advances in understanding the environments of various types of cancer caused by the participation of many chloride channel or transporters families and discuss the challenges and potential targets for cancer treatment. The modulation of chloride channels/transporters might promote new aspect of cancer treatment strategies.
Gems from the Work of Georgia Benkart

Georgia Benkart completed her PhD in 1974 at Yale University, where she was the 30th of Nathan Jacobson’s 34 PhD students. From there she joined the faculty at the University of Wisconsin–Madison, where she is now Professor Emerita. Since her retirement from teaching she has provided tremendous service to the mathematical community, notably as President of the AWM and as an Associate Secretary of the AMS for more than a decade. In this article we highlight a few selected gems from her extensive contribution to our field, organized in a roughly chronological sequence of vignettes and images (which can be read or viewed in any order). Our hope is that we can capture and transmit a snapshot of Georgia’s rich