Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dialogical Emotion Decoder for Speech Motion Recognition in Spoken Dialog

Developing a robust emotion speech recognition (SER) system for human dialog is important in advancing conversational agent design. In this paper, we proposed a novel inference algorithm, a dialogical emotion decoding (DED) algorithm, that treats a dialog as a sequence and consecutively decode the emotion states of each utterance over time with a given recognition engine. This decoder is trained by incorporating intra- and inter-speakers emotion influences within a conversation. Our approach achieves a 70.1% in four class emotion on the IEMOCAP database, which is 3% over the state-of-art model. The evaluation is further conducted on a multi-party interaction database, the MELD, which shows a similar effect. Our proposed DED is in essence a conversational emotion rescoring decoder that can also be flexibly combined with different SER engines.
Tetranychus evansi spider mite populations suppress tomato defenses to varying degrees

Abstract Plant defense suppression is an offensive strategy of herbivores, in which they manipulate plant physiological processes to increase their performance. Paradoxically, defense suppression does not always benefit the defense‐suppressing herbivores, because lowered plant defenses can also enhance the performance of competing herbivores and can expose herbivores to increased predation. Suppression of plant defense may therefore entail considerable ecological costs depending on the presence of competitors and natural enemies in a community. Hence, we hypothesize that the optimal magnitude of suppression differs among locations. To investigate this, we studied defense suppression across populations of Tetranychus evansi spider mites, a herbivore from South America that is an invasive pest of solanaceous plants including cultivated tomato, Solanum lycopersicum, in other parts of the world. We measured the level of expression of defense marker genes in tomato plants after infestation with mites from eleven different T. evansi populations. These populations were chosen across a range of native (South American) and non‐native (other continents) environments and from different host plant species. We found significant variation at three out of four defense marker genes, demonstrating that T. evansi populations suppress jasmonic acid‐ and salicylic acid‐dependent plant signaling pathways to varying degrees. While we found no indication that this variation in defense suppression was explained by differences in host plant species, invasive populations tended to suppress plant defense to a smaller extent than native populations. This may reflect either the genetic lineage of T. evansi—as all invasive populations we studied belong to one linage and both native populations to another—or the absence of specialized natural enemies in invasive T. evansi populations.
Quantification of amino groups on halloysite surfaces using the Fmoc-method

The functionalization of halloysite nanotube (HNT) surfaces with aminosilanes is an important strategy for their further decoration with organic molecules to obtain hybrid inorganic–organic nanoarchitectures to be used in catalysis and drug delivery. The exact quantification of amino groups on the surface is an important aspect in view of the obtainment of systems with a known number of loaded molecules. In the present study, we describe a simple and reliable method for the correct quantification of groups present on HNT surfaces after their reaction with aminopropyltriethoxysilane (APTES). This method, applied for the first time to HNT chemistry, was based on the use of Fmoc groups as probes covalently bound to APTES and quantified by UV-Vis after release from the HNT–APTES–Fmoc system. Interestingly, this method showed great accordance with the already employed quantitative thermogravimetric analysis (TGA), with some benefits such as simple and non-destructive procedure, besides the possibility to monitor the deprotection reaction.
Entering the world with notes: Reclaiming the practices of lecturing and note making

Abstract In this article we focus on note taking as a practice that is fundamental to (higher) education. We argue that note-taking should not primarily be regarded as a method that supports effective learning, but as formative of the student herself (making her attentive and granting possibilities for self-transformation). Hence it is a practice that has educational meaning in and of itself. It is a pedagogical form in its own right. We go on arguing that the practice of lecturing can itself be seen as a form of note taking and that both phenomena are not only closely related, but also that note making and lecturing consist of reciprocal operations. Studying on the basis of one’s notes comes down to the reverse operation the teacher had to perform when preparing her lessons. Moreover, thanks to making notes during a class students have a deeply embodied sense of what it means to generate and to construct new arguments and ideas.
Land Access in the Development of Horticultural Crops in East Africa. A Case Study of Passion Fruit in Burundi, Kenya, and Rwanda

Rapid population growth in fertile agricultural lands of East Africa creates land scarcity, which has become a major hindrance to land access for the introduction of new horticultural crops. But their introduction in these areas is increasing, because of their high market price, which improves farmers’ income. As such, this research evaluated land access dynamics (availability, acquisition, and use changes) on the introduction of passion fruits in East Africa. The study used purposeful sampling to collect information from 171 passion fruit farmers from Burundi (60), Kenya (51), and Rwanda (60) through interviews during field surveys. Among the respondents from all three countries, inheritance and land purchase were the predominant modes of land access (>50% and >21%, respectively). Furthermore, the substitution of other crops by passion fruits was high (>60%) among Kenyan and Rwandan farmers, but low (18%) among Burundian farmers. Our findings indicate that land access influences the patterns of adoption of new crops, since, when limited in supply, it may require the acquisition of new land space, abandonment of other crops, or opting for mixed farming. As such, land access should be a consideration in the promotion of new crops for sustainable agricultural ventures.
Laboratory Investigations Uni-axial Cyclic Stretch Induces Cbfa1 Expression in Spinal Ligament Cells Derived from Patients with Ossification of the Posterior Longitudinal Ligament

Ossification of the posterior longitudinal lig- ament of the spine (OPLL) is characterized by ectopic bone formation in the spinal ligaments. Mechanical stress, which acts on the posterior ligaments, is thought to be an important factor in the progression of OPLL. To clarify this mechanism, we investigated the effects of in vitro cyclic stretch (120% peak to peak, at 0.5 Hz) on cultured spinal ligament cells derived from OPLL (OPLL cells) and non-OPLL (non-OPLL cells) patients. The mRNA expressions of Cbfa1 (an osteoblast-specific transcription factor), type I collagen, alkaline phospha- tase (ALP), osteocalcin and integrin b1 (a mechano- transducer) were increased by cyclic stretch in OPLL cells, whereas no change was observed in non-OPLL cells. The effects of cyclic stretch on the spinal ligament tissues derived from OPLL and non-OPLL patients were also analyzed by immunohistochemistry using an antibody against Cbfa1. The expression of Cbfa1 was increased by cyclic stretch at the center of the spinal ligament tissues of OPLL patients, whereas no change was observed in the tissues of non-OPLL patients. Furthermore, U0126, a specific inhibitor of MAPK kinase (MEK), suppressed the stretch-induced mRNA expressions of Cbfa1, ALP and type I collagen in OPLL cells. These results suggest that in OPLL cells, me- chanical stress is converted by integrin b1 into intra- cellular signaling and that Cbfa1 is activated through the MAP kinase pathway. Therefore, we propose that mechanical stress plays a key role in the progression of OPLL through an increase in Cbfa1 expression.
The Effects of Flood, Drought, and Flood Followed by Drought on Yield in Cotton

Cotton suffers from alternations of flood and drought in China. A lysimeter trial was conducted to investigate the responses of various cotton yield indices under water-stress treatments including, flood (five-day, eight-day), drought (10-day, 15-day), and five-day flood followed by 10-day drought, during the flowering and boll-forming stage. The results showed that the seed cotton yield was significantly (p < 0.05) reduced under all water-stress treatments, while the harvest index was not affected under any treatment. Significant decreases in dry matter yield, boll number, and boll hull mass were detected under flood treatments but not under drought treatments. The percentage cotton yield losses per day induced by flood and drought were 6.22% and 2.48%, respectively. Under water stress, the associations between seed cotton yield and relevant yield indices were weakened, but yield losses were still strongly related to the decreases in dry matter yield and boll number. Flood followed by drought caused significant reductions in all yield indices except harvest index; however, the reduction was much lower than the additive reductions induced by flood and drought. These results provide bases for scheduling irrigation and drainage under climate change.
Fractional Neuro-Sequential ARFIMA-LSTM for Financial Market Forecasting

Forecasting of fast fluctuated and high-frequency financial data is always a challenging problem in the field of economics and modelling. In this study, a novel hybrid model with the strength of fractional order derivative is presented with their dynamical features of deep learning, long-short term memory (LSTM) networks, to predict the abrupt stochastic variation of the financial market. Stock market prices are dynamic, highly sensitive, nonlinear and chaotic. There are different techniques for forecast prices in the time-variant domain and due to variability and uncertain behavior in stock prices, traditional methods, such as data mining, statistical approaches, and non-deep neural networks models are not suited for prediction and generalized forecasting stock prices. While autoregressive fractional integrated moving average (ARFIMA) model provides a flexible tool for classes of long-memory models. The advancement of machine learning-based deep non-linear modelling confirms that the hybrid model efficiently extracts profound features and model non-linear functions. LSTM networks are a special kind of recurrent neural network (RNN) that map sequences of input observations to output observations with capabilities of long-term dependencies. A novel ARFIMA-LSTM hybrid recurrent network is presented in which ARFIMA model-based filters having the linear tendencies better than ARIMA model in the data and passes the residual to the LSTM model that captures nonlinearity in the residual values with the help of exogenous dependent variables. The model not only minimizes the volatility problem but also overcome the over fitting problem of neural networks. The model is evaluated using PSX company data of the stock market based on RMSE, MSE and MAPE along with a comparison of ARIMA, LSTM model and generalized regression radial basis neural network (GRNN) ensemble method independently. The forecasting performance indicates the effectiveness of the proposed AFRIMA-LSTM hybrid model to improve around 80% accuracy on RMSE as compared to traditional forecasting counterparts.
Major Structural Reorganisation Most Likely Accompanies the Transient Formation
of a Physiological Electron Transfer Complex

Modelling studies coupled with experimental observations show that the transfer of electrons from trimethylamine dehydrogenase to its electron transferring flavoprotein (ETF) requires a large quaternary change in ETF. These studies describe for the first time how complex and substantial changes in quaternary structure could control interprotein electron transfer reactions, and direct electrons onto specific and ntended redox partners.
Variation in cold tolerance in F6 durum wheat [Triticum turgidum (L.) Tell. convar. durum (Desf.) Mackey] RILs and the relationships of cold tolerance with some quality parameters and genetic markers

Abstract Low temperature is one of the critical factors for determining agricultural production. Therefore, the main objective was to develop the durum wheat lines, which are tolerant to cold particularly in Central Anatolia. The recombinant inbred lines (RILs) (141) derived from F6 progeny of durum wheat, developed from Kunduru-1149 (female parent) and Cham-1 (male parent) cross, were characterized in terms of their cold tolerance both in the field and under controlled (in growth chamber) conditions. A 0–9 scale was used for the visual evaluation of cold damage under field conditions, and a quantitative measure of photochemical efficiency (Fv/Fm = variable fluorescence/maximum fluorescence) method was used for the evaluation of cold damage under controlled conditions. Seventeen RILs displayed the scores within the range of 1–2.5 in 0–9 scale evaluation, while 41 RILs showed the scores equal to or higher than 0.70 approaching to optimal (~0.83) in Fv/Fm evaluation. Some quality parameters tested and some gliadin fragments and random amplified polymorphic DNA loci showed meaningful correlations with the data of 0–9 scale and Fv/Fm ratios from lower to the medium level. The RILs considered as cold resistant; might have the potential to be used as parental lines to develop cold-resistant durum wheat varieties in the future durum wheat-breeding programmes.
Breeding Wheat for Resilience to Increasing Nighttime Temperatures

Increases in global mean temperature since 1960 are largely attributed to the rise in minimum nighttime temperatures thereby decreasing diurnal temperature variation. Increased night temperatures are known to affect crop development. A multi-year study investigating the effects of increased night temperatures on soft red winter wheat (Triticum aestivum L.) varieties was conducted during the 2015-2016 growing seasons at the University of Kentucky Spindletop Research Farm in Lexington, KY. Thirty-six cultivars and breeding lines were chosen based on their genotypes at photoperiod and vernalization loci. This material was planted in a randomized complete block experiment with two replications and two environments, control and passively warmed. To create a passively warmed environment, thermal covers were mounted to frames in plots and connected to a datalogger programmed to cover plants from dusk to dawn based on coordinate location. Night temperature increases ranged from 0.27–0.75 °C above ambient temperature. Grain yield, averaged across genotypes, was significantly reduced in the passively warmed environment by 224 kg ha−1 (p ≤ 0.05) or 6.44%; however, yield response to environment varied among genotypes with several genotypes displaying an increased yield in the warmed environment. Yield reductions may reflect reduced nitrogen utilization (9.4%; p ≤ 0.001) under increased night temperatures.
Determination of nutritional values and postharvest performance in different types of tomatoes stored under shelf-life conditions

In this study, beefsteak (cv. ‘Tybif’), heirloom (cv. ‘Yuksel Koy’) and cluster types (cv. ‘Merkur’) of tomato were harvested at breaker stage of maturity and stored at 20oC temperature and 60±5% relative humidity for comparing their ethylene production, respiration rate, postharvest performance and nutritional characteristics. Analysis for weight loss, antioxidant activity, carotenoid, flavonoid, total phenolics, ascorbic acid contents, ethylene production, respiration rates and amount of unmarketable fruits were determined during 21 days of storage. Weight loss, ethylene production, respiration rate, carotenoid content and amount of unmarketable fruits exhibited increase whereas flavonoid and ascorbic acid content showed decrease with extending storage duration. Maximum antioxidant activity, carotenoid, total phenolics and ascorbic acid contents and minimum weight loss, ethylene production and respiration rate were noted in beefsteak type of tomatoes. Based on results obtained it can be concluded that beefsteak type of tomatoes can be successfully stored with maximal nutritional quality for 21 days of storage as compared to heirloom and cluster types of tomatoes.
A hydrothermally synthesized MoS2(1−x)Se2x alloy with deep-shallow level conversion for enhanced performance of photodetectors

Photoelectric detectors based on binary transition metal chalcogenides have attracted widespread attention in recent years. However, due to the high-temperature synthesis of binary TMD, high-density deep-level defect states may be generated, leading to poor responsiveness or a long response time. Besides, the addition of an alloy will change the DLDSs from deep to shallow energy levels caused by S vacancies. In this paper, MoS2(1−x)Se2x nanostructures were synthesized by a hydrothermal method, and a novel type of photodetector was fabricated by using the synthesized material as a light sensitive material. The MoSSe-based photodetector not only has a high photocurrent, but also exhibits a wide spectral response in the range of 405 nm to 808 nm. At the same time, it can achieve a responsivity of 1.753 mA W−1 under 660 nm laser irradiation of 1.75 mW mm−2. Therefore, this work can be considered as a method of constructing a new type of photodetector with a simple process and low cost.
Validation of inverse stereology generation of two dimensional area gradations for computational modelling of asphalt mixtures

Over the last few years, several researchers have employed computational methods to model and investigate the overall behaviour of asphalt mixture composites and different factors that influence this behaviour. Two-dimensional models, particularly those with computationally generated geometries, are commonly used in lieu of three-dimensional models due to their computational efficiency. When building these types of models, it is critical to properly determine a two-dimensional area distribution of aggregates in a given cross section, which needs to be generated from a representative three-dimensional volumetric gradation. This can be typically achieved using some form of mathematical transformation; one type of transformation often used for asphalt mixture gradations is inverse stereology. The goal of this study was to determine the effectiveness of the inverse stereology approach when compared with the true two-dimensional area gradation observed in laboratory compacted HMA specimens. The results from this study show that an inverse stereology approach based on a polyhedron shape was effective in replicating the two-dimensional area gradation created by cutting a laboratory specimen. In addition, the aspect ratio of particles was considered based on cutting the specimens vertically and horizontally; it was determined that no substantial difference existed between the vertical and horizontal cut specimens. However, it was also confirmed that the aspect ratios obtained using aggregate imaging are not representative of aspect ratios in a two dimensional cross-section of an asphalt mixture. An inverse stereology approach to converting aspect ratios from 2D to 3D provided better results, but was still not accurately able to represent the distribution of aspect ratios of aggregates.
A Silicon Nanowire Ferroelectric Field‐Effect Transistor

The design and characterization of a Schottky‐type ferroelectric field‐effect transistor based on a nominally undoped silicon nanowire are reported. The nanowire transistor is fabricated by top‐down technology starting from a silicon‐on insulator wafer. A thin ferroelectric Hf0.38Zr0. 62O2 layer is integrated via a gate‐first approach. Abrupt Schottky source/drain contacts to the undoped silicon are provided by NiSi2 formation. Two distinct nonvolatile transistor states (programmed and erased) are observed in correspondence to negative and positive polarization in the ferroelectric layer, delivering a memory window of ≈1.5 V and, differently to conventional ferroelectric field effect transistors, yielding an on‐current difference of up to 30%. These results are interpreted as a combination of effects, arising from the proximity of the ferroelectric layer to both the channel and the Schottky‐junction regions. The threshold voltage shift, due to a polarization field acting on the channel, adds up to a polarization field‐driven tuning of the current injection through the Schottky‐source junction. This provides a strategy for manufacturing Schottky‐type nanoscale transistors with the add‐on nonvolatile option, following a complementary metal‐oxide‐semiconductor compatible process. In particular, the device concept is of great interest for achieving nonvolatile polarity modification in reconfigurable field‐effect transistors.
Soil Carbon Dynamics under Pastures in Andean Socio-Ecosystems of Colombia

Models can help to explain the main interactions, magnitudes, and velocity by which biological processes accumulate soil organic carbon (SOC) in pastures. An explanatory model using Insight Maker software was constructed for each soil under natural and cultivated pastures, using theoretical carbon models and data which were collected monthly in andisol sites. The model was calibrated and validated by comparing the modeled data to the field data until the smallest prediction error was reached. The indicators used were the mean absolute error (MAE), root-mean-square error (RMSE), mean absolute percentage error (MAPE) and the coefficient of determination (R2). In natural pasture soil, the diversification of organic inputs consistently promoted the growth of microbial biomass and metabolic efficiency. In contrast, intensive management of cultivated pastures, involving the removal of plant cover, plowing and low input of organic matter, stressed the microbial community and increased the potential carbon loss through secondary mineralization and surface runoff. The application of modeling indicated that it is necessary to improve agronomic practices in cultivated pastures, to maintain soil cover and to increase the application of organic fertilizer by 1.5 times, in order to reduce stress on the microbial biomass, accumulate SOC, minimize organic matter mineralization and reduce C losses due to surface runoff. Therefore, improving agricultural management based on the understanding of soil processes will allow increasing the potential for SOC storage, while improving pasture sustainability.