Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of the roots and starches of three cassava cultivars

Cassava (Manihot esculenta Crantz) is a plant of high genetic variability. The cultivars collected in the Amazon are highly valued for their quality and adaptability to local ecological conditions. Among the products of cassava, the most versatile and valuable is starch. The aim of this study was to obtain and characterize the starches of three cultivars of cassava (Jurara, Santarem SI and Maranhense II cultivars) produced in the state of Para, aiming at technologically harnessing this crop in that region. The roots and starches were analyzed for physicochemical properties, and the starches were morphologically characterized. In general, the roots of the three cultivars had different compositions (p0.05). All of the physicochemical parameters of the starches reached the standards set by Brazilian law. According to optical and electron microscopy, the morphology of the granules from the three starches are characteristic of native cassava starches.
Book Reviews

iliar with, for example, ideas of transference and the unconscious. Other frameworks are also drawn upon, and there is considerable emphasis on putting helping in its social and organizational context. Hawkins and Shohet present a wealth of accessible and inspiring material. The multifaceted endeavor that is supervision is laid out clearly without over-simplification. I would recommend this book to anyone involved directly in supervision or in developing supervision practices in their agency.
Occurrence and impact of Agrilus spp. and associated egg parasitoids in hazel groves of Northwest Italy

In several hazel (Corylus avellana L.) groves in the area of Langhe (Piedmont, Northwest Italy), many hazel branches suddenly withered, and in some cases, the whole tree died, with heavy economic losses for the farmers. Symptoms of jewel beetle attacks were detected on the trees. Eight Agrilus species were caught by traps from 2007 to 2009 in the surveyed hazel groves; among them, only four species have been known to develop on hazel. On the traps, Agrilus olivicolor Kiesenwetter was the most abundant species, while almost only Agrilus viridis (L.) was sampled by plant beating from 2008 to 2010. Moreover, almost all adults emerged from field‐collected hazel wood belonged to this latter species that proved to be the main responsible for the severe attacks on the hazel trees. Agrilus viridis adults emerged from late May to late June, and generally lived until the end of August, while egg masses were observed from late May to late July. The egg parasitoid Oobius zahaikevitshi Trjapitzin was found in all of the investigated groves; adults emerged already from the first egg masses collected on hazel trees in late May‐early June. O. zahaikevitshi was able to largely reduce A. viridis populations, with a parasitism rate of more than 50% in some groves. Recent attacks of A. viridis were related to a long period of drought; however, appropriate agronomic practices to minimize the effects of water stress and to conserve natural enemies, such as O. zahaikevitshi, could be more effective to protect hazel groves against boring beetle attacks.
Efficient Image Enhancement Model for Correcting Uneven Illumination Images

Images captured under varying light conditions have deficient contrast, low brightness, latent colors, and high noise. Numerous methods have been developed for image enhancement. However, these methods are only suitable for enhancing specific type of images (e.g., over-exposed or underexposed), and also fail to restore artifact-free results for various other types of images. Therefore, to meet this goal, in this paper, we present an automatic image enhancement method, which is capable of producing quality results for all types of images captured under uneven exposure conditions (e.g., backlit, non-uniform, over-exposed, one-sided illumination and night-time images). Firstly, images are categorized using a convolutional neural network (CNN) to determine their class, and different values of weight coefficients are achieved for further processing. Then, images are converted into photonegative form to obtain an initial transmission map using a bright channel prior. Next, L1-norm regularization is adopted to refine scene transmission. Besides, environmental light is estimated based on an effective filter. Finally, the image degradation model is applied to achieve enhanced results. Furthermore, post-processing of the images is comprised of two steps, such as denoising and details enhancement. The denoised model is only applied when the images are captured in extreme low-light conditions. Whereas, a smooth layer is obtained using L1-norm regularization to enhance details in partially over-and under-exposed images. Extensive experiments reveal the effectives of the proposed approach as compared to other state-of-the-art algorithms.
Whisker Development from SAC0307-Mn07 Solder Alloy

In this study, the whisker growth from SAC0307-Mn07 solder alloy was investigated. To get fast information, an ultra-thin film was vacuum evaporated from the examined solder alloy onto Cu substrates. The evaporated layer was $\sim 100 - 150$ nm thick in average with the same grain size. The layers were kept at room temperature for 28 days. Whisker growth was monitored by scanning electron microscope with some days frequency, and the layer structure under the whisker was examined on focused ion beam cuts. The large mechanical stress on the Sn layer due to the intermetallic layer growth initiated the whisker growth right after the layer deposition. However, it stopped after 2 weeks since the intermetallic grains consumed the ultra-thin Sn layer. The whisker density was extremely high $(\sim 24 \, 000 pcs./mm^{2}$). Most of the whiskers were the short nodule and hillock type, which does not mean risk in microelectronics. Therefore, the alloying of Mn into the high Sn content solder alloys have a positive effect on the reliability of the solder joints.
Effects of photoperiod and diet on diapause tendency, maturation and fecundity in Harmonia axyridis (Coleoptera: Coccinellidae)

The effects of photoperiodic conditions of larval development and adult maturation (L : D = 12 : 12 vs. 18 : 6) and different diets (sugar solution, frozen eggs of Sitotroga cerealella, different numbers of aphids Myzus persicae, and their combinations) on survival, reproductive maturation and fecundity of Harmonia axyridis were studied in laboratory conditions. The fundamental aim of the work was to distinguish between cue effect of diet (neurohormonal triggering of reproduction) and direct effect of diet (nutritional maintenance of reproduction). When adults were kept under short‐day conditions, the proportion of ovipositing females decreased and the duration of the pre‐oviposition period increased. Moreover, a strong reaction to the direction of changes in the day length was demonstrated: when larvae and pupae developed at long day and adults were transferred to short day, the proportion of ovipositing females was much lower than in individuals that were permanently kept under short‐day conditions. The percentage of ovipositing females, the rate of their reproductive maturation and the average daily fecundity gradually increased in the following succession of diets: ‘sugar + 5 aphids per day < sugar + eggs < sugar + eggs + 5 aphids per day < sugar + 100 aphids per day’. However, dissection showed that most of the non‐laying females fed on these diets (particularly those kept under long‐day conditions) have started reproductive maturation, while even first stages of oogenesis were not found in females fed on sugar solution alone. We conclude that cue effect of diet (reproductive activation) can be achieved almost independently of the number of prey consumed, while nutritional effects (the rate of reproductive maturation and fecundity) are sensitive both to the quality and quantity of food.
Effects On Polarization Characteristics of Off-Body Channels with Dynamic Users

This paper presents an analysis of the depolarization effect in off-body channels, based on a previously developed geometry-based channel model for polarized communications with dynamic users. The model considers Line-of-Sight propagation and components reflected from scatterers distributed on cylinders centered around the user. A mobility model for wearable antennas based on Fourier series is employed to take the effects of user’s motion into account. The focus is on scattered signal components, where the impact of a scatter’s position, its material properties, and the influence of user dynamics on signal depolarization are investigated. It is observed that the wearable antenna motion has a strong impact on the channel’s polarization characteristics, particularly for dynamic on-body placements, such as arms and legs. If the antenna motion is neglected, the error in cross-polarization ratio is greater than 23dB compared to a static approach. The antenna rotation during motion is found to be the dominant factor, while the corresponding displacement can be neglected, with the error not exceeding 1dB. This result justifies the channel model simplification proposed in this paper.
A stream insect detritivore violates common assumptions of threshold elemental ratio bioenergetics models

Ecologists increasingly use threshold elemental ratios (TERs) to explain and predict organism responses to altered resource C∶P or C∶N. TER calculations are grounded in diet-dependent growth, but growth data are limited for most taxa. Thus, TERs are derived instead from bioenergetics models that rely on simplifying assumptions, such as fixed organism C∶P and no P excretion at peak growth. We examined stoichiometric regulation of the stream insect detritivore Pycnopsyche lepida to assess bioenergetics model assumptions and compared bioenergetics TERC∶P estimates to those based on growth. We fed P. lepida maple and oak leaf diets along a dietary C∶P gradient (molar C∶P range = 950–4180) and measured consumption, growth, stoichiometric homeostasis (H), and elemental assimilation and growth efficiencies over a 5-wk period in the laboratory. Pycnopsyche lepida responses to varying resource C∶P depended on litter identity and were strongest among oak diets, on which growth peaked at diet C∶P = 1620. Pycnopsyche lepida fed oak litter exhibited flexible body C∶P during growth and in response to altered diet C∶P (non-strict homeostasis; H = 4.74), low P use efficiencies, and P excretion at peak growth. These trends violated common bioenergetics model assumptions and caused deviation of estimated TERC∶P from C∶P = 1620. Bioenergetics TERC∶P further varied among P. lepida of differing growth status on varying diet C∶P (overall TERC∶P range = 1030–9540). Our study identifies novel effects of nutrient enrichment and litter identity on detritivore stoichiometric regulation and supports growth-based approaches for future TER calculations.
Simplified Theoretical Model based Self-adaptive Packet Reception Rate Estimation in Sensor Networks

Real-time and accurate packet reception rate estimation is crucial for wireless sensor networks. However, existing approaches usually rely on offline data collection and training, which limits their generality. Specifically, models fitted by the test data acquired under specific conditions cannot be used in all environments and for arbitrary packet sizes. In this paper, a simplification method for the theoretical bit error rate model of IEEE 802.15. 42.4 GHz physical layer is proposed, which is about 18 to 38 times faster than the original one. Then, with the simplified model, a lightweight packet reception rate estimation approach is designed, which is self-adaptive to different environments and arbitrary packet sizes. With the proposed approach, offline data collection and training are no longer needed, which will reduce deployment cost effectively. Compared with state-of-the-art approaches, estimate error of the proposed one is reduced by 2.46%$\sim$74.97% in different environments, and by 2.46%$\sim$62.00% for different packet sizes.
Insulin-Like Growth Factor-1 and PTEN Deletion Enhance Cardiac L-Type Ca2+ Currents via Increased PI3Kα/PKB Signaling

Ca2+ influx through the L-type Ca2+ channel (ICa,L) is a key determinant of cardiac contractility and is modulated by multiple signaling pathways. Because the regulation of ICa,L by phosphoinositide-3-kinases (PI3Ks) and phosphoinositide-3-phosphatase (PTEN) is unknown, despite their involvement in the regulation of myocardial growth and contractility, ICa,L was recorded in myocytes isolated from mice overexpressing a dominant-negative p110α mutant (DN-p110α) in the heart, lacking the PI3Kγ gene (PI3Kγ−/−) or with muscle-specific ablation of PTEN (PTEN−/−). Combinations of these genetically altered mice were also examined. Although there were no differences in the expression level of CaV1.2 proteins, basal ICa,L densities were larger (P<0.01) in PTEN−/− myocytes compared with littermate controls, PI3Kγ−/−, or DN-p110α myocytes and showed negative shifts in voltage dependence of current activation. The ICa,L differences seen in PTEN−/− mice were eliminated by pharmacological inhibition of either PI3Ks or protein kinase B (PKB) as well as in PTEN−/−/DN-p110α double mutant mice but not in PTEN−/−/PI3Kγ−/− mice. On the other hand, application of insulin-like growth factor-1 (IGF-1), an activator of PKB, increased ICa,L in control and PI3Kγ−/−, while having no effects on ICa,L in DN-p110α or PTEN−/− mice. The ICa,L increases induced by IGF-1 were abolished by PKB inhibition. Our results demonstrate that IGF-1 treatment or inactivation of PTEN enhances ICa,L via PI3Kα-dependent increase in PKB activation.
Effects of organic and other management practices on soil nematode communities in tea plantation: a case study in southern China

Four major tea management practices (organic, pollution-free, conventional, and semi-natural) are employed in Chinese tea plantations at present. These practices can induce changes in the physiochemical parameters, microorganism community and enzyme activity in tea plantation soil. However, understanding of their effects on soil nematodes is still scarce. This study aimed to investigate whether and how different management practices affect the biodiversity, function, and structure of soil nematode communities in tea plantation habitats. The soil nematode community structures and ecological indices were determined from the soil samples collected more than 6 y after their respective farming practices were first applied, and different management practices did not greatly affect soil nematode community evenness or species diversity, but organic practice increased nematode trophic diversity, common species diversity, and species richness. Pollution-free practice considerably increased fungivorous nematodes, and both pollution-free and conventional practice decreased bacterivorous nematodes markedly in the subsurface layers of soil. Predator and omnivorous nematodes were found to be more abundant in semi-natural plantation. Organic practice was more sustainable and suitable for tea cultivation, with the greatest biodiversity, best nutrient conditions, higher and more stable C/N ratio and lower interference in the food web.
The NOAA Microwave Integrated Retrieval System (MiRS): Validation of Precipitation From Multiple Polar-Orbiting Satellites

This article describes a multisatellite validation study of precipitation from the microwave integrated retrieval system (MiRS). MiRS is a variational algorithm designed to process passive microwave measurements using a common core of retrieval software, and currently runs operationally on data from ten different earth-observing satellites. The primary validation was conducted for the polar-orbiting satellites SNPP, NOAA20 (both bearing the ATMS instrument), MetopB, and MetopC (both bearing the AMSUA and MHS instruments) during the period from December 1, 2018 through December 31, 2019. Validation was conducted using operational ground-based radar-rain gauge analyses from Stage-IV and multiradar multisensor (MRMS) over the continental United States. Results indicate that the precipitation estimates are largely consistent with one another and that agreement with ground-based analyses has a strong seasonal component. Warm season performance is generally higher and more stable than during the cold season. SNPP and NOAA20 estimates appeared to show slightly higher biases, outside of July and August. Frequency distributions of precipitation intensity also showed better agreement between MiRS and Stage-IV for higher precipitation rates in the warm season, highlighting the difficulty of estimating over land precipitation rates associated with stratiform precipitation systems that typically occur during the cold season. All satellites depicted the annual mean precipitation rate global distribution with good interconsistency, but with some differences possibly related to individual temporal sampling characteristics of each satellite. Summary validation statistics and scores stratified by season show that MiRS performance metrics using MRMS as a reference are largely similar to those based on using Stage-IV.
Cell wall phenolics and digestibility of normal and brown midrib maizes in different stem sections and across maturity stages

The concentration of phenolic acids and in situ disappearance of cell wall (CWISD) of normal maize and bm1, bm2, bm3 and bm4 mutants were evaluated in whole stem and stem sections at the silking and silage stages. At the silking stage, the CWISD of bm1 was similar to that of normal maize while that of bm2, bm3 and bm4 was greater; p-coumaric acid and lignin concentrations were lower in the mutants while ferulic acid varied little. At the silage stage, the composition was slightly altered but the CWISD of the mutants was notably reduced, possibly because of condensation reactions occuring with ageing. The mid-internode was the most similar in composition and degradability to the whole stem.
Fake News Detection: An Ensemble Learning Approach

Due to easy access, rapid growth, and proliferation of the information available through regular news mediums or social media, it is becoming easy for people to look for news and consume it. But on the other hand, it is becoming a daunting task to differentiate between false information and true information thus leading to widespread fake news. We can define fake news as a type of deceiving journalism and statements that are used to artifice and mislead people. Also, the credibility of social media platforms is at stake where this news is mostly shared. These types of forged information news can have serious negative societal impacts and thus their detection has become the emerging area that is attracting research attention. In this paper, we propose a model for detecting fake news by examining the accuracy of a report and predicting its authenticity. By feature extraction and forming credibility scores from the textual information, this model builds an ensemble network to learn the portrayals of news reports, authors, and titles simultaneously. Different machine learning algorithms like SVM, CNN, LSTM, KNN, and Naive Bayes are used for higher accuracy and it was observed that LSTM showed better accuracy with 97%. The performance and effectiveness of classifiers were evaluated based on their precision, recall, and F1-Score. The usage of different algorithms shows the effectiveness of performance on the dataset.
Double Deep Q-learning Based Approach for Power Flow Optimization in Distribution Networks

With the increasing concerns on the environment and fossil resources, more and more renewable energies and energy storage systems (ESS) are embedded in active distribution networks (ADN). The stochastic nature of renewable energies brings great challenges to the power system operation. In this context, a double deep Q-learning based method is proposed to optimize the power flow of ADN considering the randomness of the load demand, wind speed. Experiment results validate that the proposed approach can master the optimal management strategy of ADN under constrains. Comparison results demonstrate that the proposed data-driven method can achieve better results when dealing with the uncertainty environment.
Influences of co-creation on brand experience The role of brand engagement

The purpose of this article is to study the influence of customer co-creation participation on customers’ brand experience, brand satisfaction and brand loyalty . We apply a service logic approach in which co-creation participation refers to co-creation of customer value together with the brand, co-creation of new value with the brand and co-creation of value together with other customers within the context of the brand . The reasoning applied is that customers’ co-creation with a brand – stimulating their engagement with the brand – influences brand experience, and through that, brand satisfaction and loyalty . A study among bank customers shows that co-creation participation positively influences sensory, affective, cognitive, behavioural and relational dimensions of a brand experience . However, influences of brand experience dimensions on satisfaction and loyalty are revealed to be complex as some of the dimensions influence satisfaction positively, while others have a negative influence . Furthermore, we show that the satisfaction and loyalty effects of co-creation participation are partially mediated by brand experience . Thus, there are both indirect and direct effects on satisfaction and loyalty from customers’ co-creation participation . Implications point to the importance of carefully managing co-creation participation in order to gain competitive advantages . Companies should be careful about how brand experience is stimulated through co-creation because of the potential risk of negative effects on satisfaction and loyalty .
Dichotomania: An Obsessive Compulsive Disorder that is Badly Affecting the Quality of Analysis of Pharmaceutical Trials

Les analyses des essais cliniques emploient, trop souvent, une échelle binaire construite en sectionnant en deux parties, selon des critères plus ou moins arbitraires, une échelle originale de manière continue. Cela est même souvent proposé par les autorités d’enregistrement. Cette mauvaise habitude entraîne normalement une grande perte de précision avec la conséquence que le nombre de patients pour en tirer une conclusion utile doit être fortement augmenté. Je montre, avec des exemples, que ces pertes peuvent être très importantes et que les soi-disant avantages de cette pratique sont illusoires.
Ergodic Secrecy Rate of K -user MISO Broadcast Channel with Improved Random Beamforming

In this paper, we study the secrecy performance of multiple-input single-output (MISO) wiretap channel with random beamforming (RB), where the eavesdropper is equipped with multiple antennas. In traditional RB schemes, the transmitter utilizes only one antenna to emit information signal and adopts the rest antennas to produce a random beamforming vector for security. To make full use of the power resource and improve the secrecy performance, we propose a power-minimizing and signal-splitting random beamforming (PM-SSRB) scheme, where the random beamforming vector is generalized with arbitrary number of transmit antennas based on power-minimizing. To evaluate the secrecy performance of the proposed scheme, we analyze the ergodic secrecy rate and derive the closed-form expression of the ergodic rate of the MISO wiretap channel. Simulation results show that, compared with the traditional hybrid artificial fast-fading scheme (AFF) and artificial noise (AN) scheme, the proposed SSRB scheme and PM-SSRB scheme perform much better in terms of the ergodic secrecy rate in all power regimes. More importantly, when the eavesdropper has more antennas than the transmitter, our schemes always outperform the AFF and AN schemes. The PM-SSRB scheme is also shown to be superior to the secret-key AFF scheme.