Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Twenty Maize Germplasms from Belize, French Guiana, Guyana, and Suriname for Resistance to Leaf-Feeding Spodoptera frugiperda

Abstract. Fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), is native to the Americas and a recent invasive pest of Africa, Asia, and Oceania. The insect causes economic damage to maize (Zea mays L.) by feeding on leaf, tassel, and ear tissue. The pest is resistant to several classes of insecticide and Bt-maize grown in certain geographic areas. Native resistance in maize combined with existing control tactics could help overcome control issues. The objective for the study was to evaluate resistance to leaf-feeding fall armyworm in maize germplasm from four countries in the historical range of the pest. Plants grown in the field and artificially infested at the seven-leaf stage were visually scored for leaf-feeding damage at 7 and 14 days post infestation. Scores for Ames 28786 (‘GIN II’) maize germplasm were not different than the resistant check, GT-FAWCC(C5). In 2020 and 2021, 14-day scores for NSL 283834 (‘Guyana 807’) (5.8 ± 0.3 and 4.9 ± 0.3, respectively) were not different than GT-FAWCC(C5) (5.3 ± 0.2 and 4.8 ± 0.3, respectively). The germplasm sources are moderately resistant to leaf feeding by fall armyworm and might be useful to breeding programs developing resistant maize. In one of 2 years of testing, NSL 283833, NSL 283890, and PI 553088 germplasms received 14-day scores <6.0, and further testing is required to determine their ability to resist leaf-feeding fall armyworm. All maize germplasms tested are tropical and require breeding to adapt progeny for additional research in temperate areas.
Interaction of the Nanoparticles and Plants in Selective Growth Stages—Usual Effects and Resulting Impact on Usage Perspectives

Nanotechnologies have received tremendous attention since their discovery. The current studies show a high application potential of nanoparticles for plant treatments, where the general properties of nanoparticles such as their lower concentrations for an appropriate effects, the gradual release of nanoparticle-based nutrients or their antimicrobial effect are especially useful. The presented review, after the general introduction, analyzes the mechanisms that are described so far in the uptake and movement of nanoparticles in plants. The following part evaluates the available literature on the application of nanoparticles in the selective growth stage, namely, it compares the observed effect that they have when they are applied to seeds (nanopriming), to seedlings or adult plants. Based on the research that has been carried out, it is evident that the most common beneficial effects of nanopriming are the improved parameters for seed germination, the reduced contamination by plant pathogens and the higher stress tolerance that they generate. In the case of plant treatments, the most common applications are for the purpose of generating protection against plant pathogens, but better growth and better tolerance to stresses are also frequently observed. Hypotheses explaining these observed effects were also mapped, where, e.g., the influence that they have on photosynthesis parameters is described as a frequent growth-improving factor. From the consortium of the used nanoparticles, those that were most frequently applied included the principal components that were derived from zinc, iron, copper and silver. This observation implies that the beneficial effect that nanoparticles have is not necessarily based on the nutritional supply that comes from the used metal ions, as they can induce these beneficial physiological changes in the treated cells by other means. Finally, a critical evaluation of the strengths and weaknesses of the wider use of nanoparticles in practice is presented.
Research on The Design Method of Auto Induction Rearview Mirror

Reverse engineering is an important branch in the field of mechanical design and manufacturing. This paper introduces reverse engineering technology and its working process, including digital processing, three-dimensional modeling, manufacturing, measurement and inspection, and so on. Taking the rearview mirror of an automobile as an example, it focuses on its digital processing and modeling.
Distributed Acoustic Sensing (Das) for Detection of Defects in Dams Using Ambient Noise Interferometry

The aim of this study was to assess the capabilities of seismic Ambient Noise Interferometry (ANI) with fibre-optic Distributed Acoustic Sensing (DAS) data to monitor earthen dams. A test dam was used to assess the applicability of ANI methodology to small-scale infrastructure with imaging and monitoring of the dam using DAS data. The study highlights anomalous regions in the Älvkarleby Test Dam that may be defects. Problem areas highlighted in this way can be further assessed to determine the need for remediation work. The study demonstrates the potential to combine DAS and ANI techniques to image and monitor infrastructure and landslides at distance from a fibre-optic cable.
Transmitter Shaping for Receiver Dynamic Range Reduction in Wireline Channels

An online shaping technique for high performance communication over Gaussian channels with Inter-Symbol Interference (ISI) and receiver Analog to Digital Converter (ADC) noise is presented. The technique uses online transmitter precoding over Pulse Amplitude Modulation (PAM) constellation, designed to shape the symbols distribution so that peak power constraint at the channel output is satisfied. An iterative decoder shares information between a modified M-BCJR module, which computes online the trellis transition probabilities of the shaped distribution, and turbo decoder. The result is a reduction in the required Effective Number Of Bits (ENOB) of the receiver ADC. We show that the transmitter precoding performs channel equalization without using any filter. At the limit of very high Signal to Noise Ratio (SNR) a complete channel inversion is possible so that the receiver signal spectrum becomes almost flat. Theoretical bounds are analytically derived which enable to assess the possible gain using the proposed method. For data rates of 200 Gbps and 400 Gbps over printed circuit board, simulations show that the shaping scheme enables reduction in the ENOB requirement as high as 1.43 bit and 1.78 bit, respectively, compared to uniform 4-PAM transmission with turbo equalization at the receiver side.
Physicochemical and Functional Properties of Pectinase-treated Peel Powder from Carabao Mango (Mangifera indica cv. Carabao)

Fruit peel wastes such as from mango can be utilized as an alternative source of dietary fiber and may further be modified to improve specific functional properties. In this study, mango peel powder was treated with pectinase to produce mango peel powder with reduced hydration properties. The resulting pectinase-treated mango peel powder (PMPP) has reduced crude pectin (0.53 g/ 100 g), greater lignin (46.88 g/ 100 g extractive free solid), protein (10.86 g/ 100 g), fat (3.94 g/ 100 g), iron (8.7 mg/ 100 g), calcium (434 mg/ 100 g) and sodium (76.5 mg/ 100 g) compared to the untreated mango peel powder (MPP). Fourier transform infrared (FTIR) analysis showed the presence of new peaks and shifted signals in PMPP but not in MPP – indicative of changes in cellulose, hemicellulose, and lignin composition. PMPP exhibited lower water holding capacity (WHC) (2.20 mL g–1) and swelling capacity (SC) (4.00 mL g–1) and comparable hypoglycemic properties with psyllium and metformin. Phenolic extract from PMPP showed dose-dependent antioxidant activity but weaker free radical scavenging capacity compared to MPP. Results show that pectinase treatment improved the properties of the mango peel powder and could lead to the utilization of PMPP as a food ingredient and as a dietary fiber supplement with functional and health potential.
A TRI-BAND MINIATURIZED ANTENNA USING FRACTAL DEFECTED GROUND STRUCTURE FOR C/X AND KU-BAND APPLICATIONS

|In this article, a miniaturized antenna with a Koch fractal defected ground structure (KFDGS) is proposed for C/X and Ku-band applications. The performance of an inset-fed lambda/2 patch antenna is examined using an iterated KFDGS etched on the ground plane. A conventional antenna operated at 16 GHz with a return loss of (cid:0) 34 : 31 dB is constructed, followed by a tri-band miniaturized antenna operating at 6.35, 9, and 13.05 GHz with a return loss of (cid:0) 22 : 41, (cid:0) 25 : 05, and (cid:0) 28 : 54 dB in order to achieve miniaturization of 60.31%, 43.75%, and 18.43%, respectively. An antenna is designed on a Roger RT Duroid substrate, fabricated, and tested with dimensions of 12 (cid:2) 14 (cid:2) 0 : 8 mm 3 , and its impact on reduction in size performance has been evaluated with measured peak directivity and gain of 3.07 and 2.80 dBi at 6.35 GHz, 4.78 and 4.65 dBi at 9 GHz, and 7.73 and 7.76 dBi at 13.05 GHz, respectively. A good agreement is found between the measurements and simulations.
Production characteristics of obstruents in WaveNet and older TTS systems

Segmental properties of Text-To-Speech (TTS) synthesizers have been studied for their influence on various perceived attributes of synthesized speech. However, they have received very limited attention for modern, neural vocoder-based TTS. In this paper, we compare segmental properties of WaveNET vocoder voices with a natural voice, and the best-performing non-neural synthesizers of the 2013 Blizzard Challenge. We extended the 2013 dataset with two new voices generated using a WaveNET vocoder. Acoustic-phonetic features of obstruent consonants and their neighbouring vowels were compared be-tween the natural voice and each of these TTS systems. Statistical analysis was conducted using the Kruskal-Wallis test, and Dunn’s test. Compared to the reference natural voice, we find that the WaveNET vocoder performs very well in modelling vowels, but features like F0 at onset and spectral tilt show significant deviations from the natural voice. Among consonants, neural voices deviate most from natural in the context of voiceless fricatives. Compared to other TTS systems, several features (like vowel dispersions, and consonant duration) which had shown strong deviations from natural, were found to not differ from natural in the WaveNET vocoder systems.
Brightness Observations of the Sun

There are few solar surface brightness observations with sufficient accuracy to have direct bearing on the question of the origin of the Sun's bolometric luminosity and irradiance changes (the cor relative observations have been reviewed elsewhere in these proceedings). This paper contrasts these observations with a model for the solar variability and illustrates our clear need for high precision surface photometry, in combination with helioseismic data and numerical experiments.
Build Loyalty with Islamic Relationship Marketing and Trust Through Satisfaction

This study examines and explains how loyalty is built with Islamic relationship marketing and trust through customer satisfaction. The success of a company in getting satisfied customers will have an impact on customer loyalty. Although relationship marketing research is a popular topic, research on relationship marketing from an Islamic perspective is very limited. Relationship marketing from an Islamic perspective is interesting because it is very relevant to be practiced in today's business development. The quantitative approach used in this study, the data collection method through questionnaires with non-probability sampling techniques, the number of respondents was 76, the data analysis technique used in this study was Path Analysis. The results showed that there was a relationship between Islamic relationship marketing and trust which had a direct effect on customer satisfaction. Islamic relationship marketing and trust directly affect loyalty, and consumer satisfaction has a direct effect on loyalty. Consumer satisfaction can play a role as a mediating variable between Islamic relationship marketing and trust on loyalty.
Intraoperative assessment of parathyroid perfusion using indocyanine green angiography in robotic thyroidectomy

In recent da Vinci robot systems (Intuitive Surgical), near-infrared fluorescence imaging (Firefly technology) has been used. With this technique, it is possible for surgeons to see important structures well beyond the limits of their eyes; hence, surgeons can safely operate and make critical decisions accurately using image-guided surgery. Because parathyroid glands (PTGs) are small and embedded in the surrounding tissues, such as lymph nodes and fat, it is often very hard for surgeons to identify PTGs. To preserve PTGs well, the surgeon must be able to accurately identify PTGs, preserve the vasculature surrounding, and maintain the perfusion to PTGs. Herein, we report an assessment of PTG perfusion using indocyanine green angiography in transoral robotic thyroidectomy.
Advanced Speaker Embedding with Predictive Variance of Gaussian Distribution for Speaker Adaptation in TTS

Speaker adaptation in text-to-speech (TTS) has three goals: high-quality audio, requirement of a small amount of data for adapting to a new speaker, and fine-tuning few parameters for storage efficiency in commercial service of custom voice. In this paper, we introduce a novel adaptation method to achieve the aforementioned three goals. First, we estimate variances from a speaker embedding and add them back to the speaker embedding. Through this operation, the distribution of each speaker in latent space increases. Moreover, we design a prediction model that could generate a speaker embedding that approximately represents the new speaker’s timbre. We can obtain a new speaker embedding well representing the timbre of a new speaker by the search process to the starting point of fine-tuning and the prediction model. We observe the performance change according to the number of fine-tuning parameters. Finally, we evaluate the proposed method using the mean opinion score (MOS) to demonstrate the remarkable performance of our proposed method.
Assessing Quantitatively Interpretable Zones From 1D Forward Modelling Aem Inversion Models

The inversion of time-domain AEM data with full 3D inversion requires specialists’ expertise and a huge amount of computational resources, not readily available to everyone. Consequently, quasi-2D/3D inversion methods are prevailing, using a much faster but approximate (1D) forward model. The question remains whether the obtained inversion results are reliable and can be interpreted quantitatively. We propose an appraisal tool for quasi-2D/3D methods that indicate zones in the inversion model that are not in agreement with the multidimensional (2D/3D) forward model and therefore, should not be interpreted in a quantitative fashion. The image appraisal step only requires one full 2.5D or 3D forward and one multidimensional Jacobian computation on a coarse mesh to compute a so-called normalized gradient. Large values in that gradient indicate model parameters that do not fit the true multidimensionality of the observed data well and should not be interpreted quantitatively. We demonstrate our method on a real AEM survey in a salinization context, revealing problematic zones in the fresh-saltwater interface. Interestingly, the problematic zones are not necessarily at larger depths, but where the interface is changing. The advantage of our approach is that all computations are feasible on a single laptop.
An Improved Transformer Transducer Architecture for Hindi-English Code Switched Speech Recognition

Due to the extensive usage of technology in many languages throughout the world, interest in Automatic Speech Recognition (ASR) systems for Code-Switching (CS) in speech has grown in recent years. Several studies have shown that End-to-End (E2E) ASR is easier to adopt and works much better in monolingual settings. E2E systems are likewise widely recognised for requiring massive quantities of labelled speech data. Since there is a scarcity in the availability of large amount of CS speech, E2E ASR takes longer computation time and does not offer promising results. In this work, an E2E ASR model system using a transformer-transducer architecture is introduced for code-switched Hindi-English speech, and also addressed training data scarcity by leveraging the vastly available monolingual data. Specifically, the language-specific modules in the Trans-former are pre-trained by leveraging the vastly available single language speech datasets. The proposed method also provides a Word Error Rate (WER) of 29.63% and Transliterated Word Error Rate (T-WER) of 27.42% which is better than the state-of-the-art by 2.19% .
MARKETING STIMULI AND PURCHASE BEHAVIOR OF CUSTOMERS FOR SMART PHONES: A CLOSER LOOK AT CONSUMER INVOLVEMENT

The study has used the claims of S-O-R model regarding consumer behavior and investigates the impact of marketing stimuli on purchase behavior of Smartphone users, to add value in the concept; researcher has conceptualized the consumer involvement as a mediator between the relationships. A sample of 318 Smartphone users responded through convenient sampling technique. The findings of the research unfold that marketing stimuli has positive impact on both consumer involvement and purchase behavior. Whereas consumer involvement does mediate the relationship between marketing stimuli and purchase behavior. The major contribution of this research is that it provides deep insight into use of marketing stimuli in studying consumer purchase behavior. Further studies should prioritize the dimensions of marketing stimuli with respect to their impact on consumer involvement and purchase behavior.
ema2wav: doing articulation by Praat

In this paper, we present ema2wav , a software conversion tool for electromagnetic articulographic data, producing multi-channel WAVE files. The data can be converted either by executing a stand-alone Python script or by using a user-friendly GUI. ema2wav allows the display and extraction of EMA trajectories as well as data smoothing and the computation of derivatives and Euclidean distances between sensors. A great asset of this converter is that it allows the research community to process EMA data in widespread and easy-to-use open-source programs like Praat . It is completely platform-independent and is thus a very promising alternative for e.g., students, teachers and researchers in experimental linguistics who have either limited access to software licenses and/or seek for an easy way to maintain open solutions for their research.
FlowCPCVC: A Contrastive Predictive Coding Supervised Flow Framework for Any-to-Any Voice Conversion

Recently, the research of any-to-any voice conversion(VC) has been developed rapidly. However, they often suffer from unsat-isfactory quality and require two stages for training, in which a spectrum generation process is indispensable. In this paper, we propose the FlowCPCVC system, which results in higher speech naturalness and timbre similarity. FlowCPCVC is the first one-stage training system for any-to-any task in our knowledge by taking advantage of VAE and contrastive learning. We employ a speaker encoder to extract timbre information, and a contrastive predictive coding(CPC) based content extractor to guide the flow module to discard the timbre and keeping the linguistic information. Our method directly incorporates the vocoder into the training, thus avoiding the loss of spectral information as in two-stage training. With a fancy method in training any-to-any task, we can also get robust results when using it in any-to-many conversion. Experiments show that FlowCPCVC achieves obvious improvement when compared to VQMIVC which is current state-of-the-art any-to-any voice conversion system. Our demo is available online 1 .
Online Context-Aware Task Assignment in Mobile Crowdsourcing via Adaptive Discretization

Mobile crowdsourcing is rapidly boosting the Internet of Things revolution. Its natural development leads to an adaptation to various real-world scenarios, thus imposing a need for wide generality on data-processing and task-assigning methods. We consider the task assignment problem in mobile crowdsourcing while taking into consideration the following: (i) we assume that additional information is available for both tasks and workers, such as location, device parameters, or task parameters, and make use of such information; (ii) as an important consequence of the worker-location factor, we assume that some workers may not be available for selection at given times; (iii) the workers' characteristics may change over time. To solve the task assignment problem in this setting, we propose <italic>Adaptive Optimistic Matching for Mobile Crowdsourcing</italic> (AOM-MC), an online learning algorithm that incurs <inline-formula><tex-math notation="LaTeX">$\tilde{O}(T^{(\bar{D}+1)/(\bar{D}+2)+\epsilon })$</tex-math></inline-formula> regret in <inline-formula><tex-math notation="LaTeX">$T$</tex-math></inline-formula> rounds, for any <inline-formula><tex-math notation="LaTeX">$\epsilon >0$</tex-math></inline-formula>, under mild continuity assumptions. Here, <inline-formula><tex-math notation="LaTeX">$\bar{D}$</tex-math></inline-formula> is a notion of dimensionality which captures the structure of the problem. We also present extensive simulations that illustrate the advantage of adaptive discretization when compared with uniform discretization, and a time- and location-dependent crowdsourcing simulation using a real-world dataset, clearly demonstrating our algorithm's superiority to the current state-of-the-art and baseline algorithms.
Adsorption and diffusion properties of calcium ions at the van der Waals interface of NbSe2-graphene 2D heterostructure for multivalent battery applications: density functional theory calculations

Multivalent-ion batteries such as calcium-ion batteries show promise as a high-density alternative to lithium-ion batteries which currently dominate the portable electronics market. In this work, the adsorption and diffusion properties of calcium ion at the van der Waals (vdW) interface of the 2D heterostructure formed by vertically stacking NbSe2 monolayer and graphene were investigated via density functional theory (DFT) calculations. Results showed that calcium can be effectively adsorbed on the vdW interface of the 2D heterostructure, with the binding energy of most stable site at −2.77 eV, much higher than most metal ions’ binding on pristine graphene. Thus, the NbSe2-graphene 2D heterostructure reinforced the binding of calcium ions at the interface. It is revealed that due to the random stacking nature of NbSe2 and graphene, a multi-path minimum energy pathways were identified at the van de Waals region, with relatively low diffusion barriers of around 0.20–0.50 eV. These indicate the capabilities of the 2D vdW heterostructure for fast multivalent ionic mobility and charge-discharge rate, while maintaining strong binding at the vdW interface. The results reveal NbSe2-graphene 2D vdW heterostructure’s potential as a promising anode material for multivalent battery applications.
Large-scale properties of the interplanetary magnetic field

The influence of time variations in the solar-wind velocity upon the configuration of the interplanetary magnetic field is discussed. Such variations may cause the persistent (approx. =2 days) departures of the field vector from the spiral direction, the ''kink'' configurations, and the decrease in the sector-averaged angle defining the interplanetary field direction. (AIP)