Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Potential and Inheritance Patterns of Physiological, Agronomic and Quality Traits in Bread Wheat under Normal and Water Deficit Conditions

Water scarcity is a major environmental stress that adversatively impacts wheat growth, production, and quality. Furthermore, drought is predicted to be more frequent and severe as a result of climate change, particularly in arid regions. Hence, breeding for drought-tolerant and high-yielding wheat genotypes has become more decisive to sustain its production and ensure global food security with continuing population growth. The present study aimed at evaluating different parental bread wheat genotypes (exotic and local) and their hybrids under normal and drought stress conditions. Gene action controlling physiological, agronomic, and quality traits through half-diallel analysis was applied. The results showed that water-deficit stress substantially decreased chlorophyll content, photosynthetic efficiency (FV/Fm), relative water content, grain yield, and yield attributes. On the other hand, proline content, antioxidant enzyme activities (CAT, POD, and SOD), grain protein content, wet gluten content, and dry gluten content were significantly increased compared to well-watered conditions. The 36 evaluated genotypes were classified based on drought tolerance indices into 5 groups varying from highly drought-tolerant (group A) to highly drought-sensitive genotypes (group E). The parental genotypes P3 and P8 were identified as good combiners to increase chlorophyll b, total chlorophyll content, relative water content, grain yield, and yield components under water deficit conditions. Additionally, the cross combinations P2 × P4, P3 × P5, P3 × P8, and P6 × P7 were the most promising combinations to increase yield traits and multiple physiological parameters under water deficit conditions. Furthermore, P1, P2, and P5 were recognized as promising parents to improve grain protein content and wet and dry gluten contents under drought stress. In addition, the crosses P1 × P4, P2 × P3, P2 × P5, P2 × P6, P4 × P7, P5 × P7, P5 × P8, P6 × P8, and P7 × P8 were the best combinations to improve grain protein content under water-stressed and non-stressed conditions. Certain physiological traits displayed highly positive associations with grain yield and its contributing traits under drought stress such as chlorophyll a, chlorophyll b, total chlorophyll content, photosynthetic efficiency (Fv/Fm), proline content, and relative water content, which suggest their importance for indirect selection under water deficit conditions. Otherwise, grain protein content was negatively correlated with grain yield, indicating that selection for higher grain yield could reduce grain protein content under drought stress conditions.
Perilaku Konsumen Rumah Tangga Dalam Memilih Daging Sapi di Kota Padang (The Behavior of Household Consumers in Choosing The Beef in Padang)

Penelitian dilakukan dengan menggunakan metode survei. Responden penelitian adalah ibu rumah tangga yang ada di kota Padang. Teknik pengambilan sampel secara cluster random sampling berdasarkan wilayah pemukiman yang dibagi menjadi wilayah pusat kota dan wilayah pinggiran kota. Jumlah sampel ditentukan secara quota sebanyak 120 orang yang dipilih dengan metode accidental . Hasil penelitian menunjukkan bahwa perilaku ibu rumah tangga dalam memilih daging sapi ditinjau dari aspek fisik daging secara keseluruhan responden memilih daging segar (100%), dari aspek kualitas daging rata-rata responden memilih mengkonsumsi daging padat (76,7%) dan dari aspek harga sangat mempengaruhi konsumen rumah tangga untuk memilih mengkonsumsi daging sapi atau tidak (100%). Kata kunci: perilaku, daging sapi, konsumen rumah tangga, padang
Direct observations indicate photodegradable oxygenated volatile organic compounds (OVOCs) as larger contributors to radicals and ozone production in the atmosphere

Abstract. Volatile organic compounds (VOCs) regulate atmospheric oxidation capacity, and the reactions of VOCs are key in understanding ozone formation and its mitigation strategies. When evaluating their impact, most previous studies did not fully consider the role of oxygenated VOCs due to limitations of measurement technology. By using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) combined with a gas chromatograph–mass spectrometer (GC–MS), a large number of oxygenated VOCs (OVOCs) have been quantified in Guangzhou city, China. Based on the new dataset, we demonstrate that constraints using OVOC observations are essential in modeling radical and ozone production, as modeled OVOCs can be substantially lower than measurements, potentially due to primary emissions and/or missing secondary sources. Non-formaldehyde (HCHO) OVOCs can contribute large fractions (22 %–44 %) of total ROx radical production, which are comparable to or larger than the contributions from nitrous acid and formaldehyde. Our results show that models without OVOC constraints using ambient measurements will underestimate the production rates of ROx and ozone, and they may also affect the determination of sensitivity regime in ozone formation. Therefore, a thorough quantification of photodegradable OVOC species is in urgent need to understand accurately the ozone chemistry and to develop effective control strategies.
An Expeditious Approach towards the Synthesis and Application of Water-Soluble and Photostable Fluorogenic Chromones for DNA Detection

The intensive research for hybridization probes based on organic molecules with fluorogenic properties is currently attracting particular attention due to their potential to efficiently recognize different DNA conformations and the local environment. However, most established organic chromophores do not meet the requirements of this task, as they do not exhibit good brightness in aqueous buffer media, develop aggregation and/or are not easily conjugated to oligodeoxynucleotides (ODNs) while keeping their photophysics intact. Herein, an important modification strategy was employed for a well-known fluorophore, 2-(4-(diethylamino)phenyl)-3-hydroxychromone (dEAF). Although this push–pull dye absorbs intensively in the visible range and shows emission with large Stokes shifts in all organic solvents, it is strongly quenched in water. This Achilles’ heel prompted us to implement a new strategy to obtain a series of dyes that retain all the photophysical features of dEAF in water, conjugate readily with oligonucleotides, and furthermore demonstrate sensitivity to hydration, thus paving the way for a high-performance fluorogenic DNA hybridization probe.
Estimation of Soil Organic Carbon Content in the Ebinur Lake Wetland, Xinjiang, China, Based on Multisource Remote Sensing Data and Ensemble Learning Algorithms

Soil organic carbon (SOC), as the largest carbon pool on the land surface, plays an important role in soil quality, ecological security and the global carbon cycle. Multisource remote sensing data-driven modeling strategies are not well understood for accurately mapping soil organic carbon. Here, we hypothesized that the Sentinel-2 Multispectral Sensor Instrument (MSI) data-driven modeling strategy produced superior outcomes compared to modeling based on Landsat 8 Operational Land Imager (OLI) data due to the finer spatial and spectral resolutions of the Sentinel-2A MSI data. To test this hypothesis, the Ebinur Lake wetland in Xinjiang was selected as the study area. In this study, SOC estimation was carried out using Sentinel-2A and Landsat 8 data, combining climatic variables, topographic factors, index variables and Sentinel-1A data to construct a common variable model for Sentinel-2A data and Landsat 8 data, and a full variable model for Sentinel-2A data, respectively. We utilized ensemble learning algorithms to assess the prediction performance of modeling strategies, including random forest (RF), gradient boosted decision tree (GBDT) and extreme gradient boosting (XGBoost) algorithms. The results show that: (1) The Sentinel-2A model outperformed the Landsat 8 model in the prediction of SOC contents, and the Sentinel-2A full variable model under the XGBoost algorithm achieved the best results R2 = 0.804, RMSE = 1.771, RPIQ = 2.687). (2) The full variable model of Sentinel-2A with the addition of the red-edge band and red-edge index improved R2 by 6% and 3.2% over the common variable Landsat 8 and Sentinel-2A models, respectively. (3) In the SOC mapping of the Ebinur Lake wetland, the areas with higher SOC content were mainly concentrated in the oasis, while the mountainous and lakeside areas had lower SOC contents. Our results provide a program to monitor the sustainability of terrestrial ecosystems through a satellite perspective.
ENHANCING COLLECTIVE CREATIVE DESIGN? AN EXPLORATORY STUDY BASED ON A DYNAMIC PERSONA IN A VIRTUAL ENVIRONMENT

This paper describes an exploratory study to determine the influence of using a dynamic persona in a virtual environment on creative design activities. A pilot group composed of two professionals (a designer and an ergonomist) and a dynamic persona had to perform a creative task. We compared both their creative performance and group dynamic with those of 11 groups of three participants who performed the same task, in the same virtual environment, with the same communication modality (i.e., chat). Results tend to show slightly more ideas as well as higher originality of ideas in the dynamic persona group than in the other groups (without any persona). We also observed, in the dynamic persona condition, a satisfying quality of collaboration and level of empathy toward the dynamic persona.
Using association rule mining to enrich user profiles with research paper recommendation

Association rules are used in recommender systems to develop a model that enhances the profiles of users, as well as to address the cold start problem. Our approach proposes a model which is implemented in a system for recommending scientific papers called Collaborative Topic Regression (CTR). Collaborative Topic Regression consists of two matrices, U and V, where U represents the relationship between users and paper topics, while V represents the relationship between papers and the paper topics. The CTR model is focused on matrix V, by adopting it, and as the result, it is influenced by the paper’s textual content, leaving the content of matrix U essentially unchanged. The depicted model extracts association rules from matrix U, and then enriches it, with the information gleaned from the mining process. The outcomes are based on both, out-of-matrix prediction and in-matrix prediction. Our approach improved the quality of the results by up to 20% for out-of-matrix prediction in the best-case scenario. Unfortunately, the same cannot be said for in-matrix prediction, which will be further investigated in the future.
Confusing Context with Character: Correspondence Bias in Economic Interactions

When drawing inferences about a person’s personal characteristics from the person’s actions, “correspondence bias” is the tendency to overestimate the influence of those characteristics and underestimate the influence of situational factors, such as incentives the individual faces. We build a simple framework to formalize correspondence bias and test its predictions in an online experiment. Consistent with correspondence bias, subjects are, on average, willing to pay to receive the dictator-game givings of an individual with whom they are randomly assigned to play a game that encourages cooperation rather than one with whom they play a game that encourages selfish behavior. We show, further, that experiencing both games oneself, as opposed to playing one and observing the other, reduces the bias, and receiving information about how each of the players behaved in both games eliminates it. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
Microbiological and Physicochemical Analysis of Old Sokoto Abattoir Wastewater (Sewage) Contaminated with Blacksmith Activities

The physicochemical and microbiological characteristics of wastewater samples from Old Sokoto Abattoir in Sokoto North Local Government Area, Sokoto state, Nigeria were studied over four weeks period. The physicochemical parameters of the wastewater samples studied namely pH, temperature, biochemical oxygen demand (BOD), dissolved oxygen (DfO), phosphate, nitrate, and chemical oxygen demand (COD) were within the standard limit for wastewater to be discharged into the environment. Heavy metals like nickel, copper, and lead were not detected (ND) except for iron with a concentration range from 0-0.64 mg/L. Wastewater samples for week 1 had a higher bacterial count of 270x105 CFU/mL than wastewater samples for the other weeks. The total viable count for all the samples exceeded the limit of 1x102 CFU/mL, which was between 4.1x105 â€“ 27.0x105. All the wastewater samples were found to harbour coliform organisms in numbers greater than the required WHO standard (1x102 CFU/mL) for water. The MPN count of wastewater was ranged from 190-1100 MPN/100 mL. The bacterial species isolated were E. coli (33.3%), E. aerogenes (20%), S. aureus (6.66%), K. pneumoniae (6.66%), Proteus vulgaris (13.3%), Citrobater freundii (6.66%), Bacillus licheniformis (6.66%), and Bacillus spp. The fungal isolates were Mucor spp (12.5%), Aspergillus niger (37.5%), Aspergillus terreus (12.5%), Sporothrix schenkii (12.5%), Rhodotorula spp. (12.5%), and Penicillium spp. (12.5%). This study showed that the isolation and population of microorganisms from wastewater in Old Sokoto Abattoir is an indication that the wastewater was highly polluted with microbial load and can cause an environmental hazard if not treated.
Sparse-Input Neural Networks to Differentiate 32 Primary Cancer Types on the Basis of Somatic Point Mutations

Background and Objective: This paper aimed to differentiate primary cancer types from primary tumor samples on the basis of somatic point mutations (SPMs). Primary cancer site identification is necessary to perform site-specific and potentially targeted treatment. Current methods such as histopathology and lab tests cannot accurately determine cancer origin, which results in empirical patient treatment and poor survival rates. The availability of large deoxyribonucleic acid sequencing datasets has allowed scientists to examine the ability of somatic mutations to classify primary cancer sites. These datasets are highly sparse since most genes will not be mutated, have a low signal-to-noise ratio, and are often imbalanced since rare cancers have fewer samples. Methods: To overcome these limitations a sparse-input neural network (SPINN) is suggested that projects the input data in a lower-dimensional space, where the more informative genes are used for learning. To train and evaluate SPINN, an extensive dataset for SPM was collected from the cancer genome atlas containing 7624 samples spanning 32 cancer types. Different sampling strategies were performed to balance the dataset. SPINN was further validated on an independent ICGC dataset that contained 226 samples spanning four cancer types. Results and Conclusions: SPINN consistently outperformed classification algorithms such as extreme gradient boosting, deep neural networks, and support vector machines, achieving an accuracy up to 73% on independent testing data. Certain primary cancer types/subtypes (e.g., lung, brain, colon, esophagus, skin, and thyroid) were classified with an F-score > 0.80.
Food Contamination: An Unexplored Possible Link between Dietary Habits and Parkinson’s Disease

Importance of a healthy lifestyle in maintaining the population’s well-being and health, especially in terms of balanced nutrition, is well known. Food choice of and dieting habits could impact disease management, which is especially true for Parkinson’s disease (PD). However, nowadays, it is not that simple to maintain a balance in nutrition, and the idea of a healthy diet tends to fade as the consequence of a western lifestyle. This should not only be dealt with in the context of food choice, but also from an environmental point of view. What we put into our bodies is strictly related to the quality of ecosystems we live in. For these reasons, attention should be directed to all the pollutants, which in many cases, we unknowingly ingest. It will be necessary to explore the interaction between food and environment, since human activity also influences the raw materials destined for consumption. This awareness can be achieved by means of an innovative scientific approach, which involves the use of new models, in order to overcome the traditional scientific investigations included in the study of Parkinson’s disease.
PDGF/PDGFR: A Possible Molecular Target in Scleroderma Fibrosis

Systemic sclerosis (SSc) is a clinically heterogeneous disorder of the connective tissue characterized by vascular alterations, immune/inflammatory manifestations, and organ fibrosis. SSc pathogenesis is complex and still poorly understood. Therefore, effective therapies are lacking and remain nonspecific and limited to disease symptoms. In the last few years, many molecular and cellular mediators of SSc fibrosis have been described, providing new potential options for targeted therapies. In this review: (i) we focused on the PDGF/PDGFR pathway as key signaling molecules in the development of tissue fibrosis; (ii) we highlighted the possible role of stimulatory anti-PDGFRα autoantibodies in the pathogenesis of SSc; (iii) we reported the most promising PDGF/PDGFR targeting therapies.
Experimental and analytical study of highly tunable electrostatically actuated resonant beams

We demonstrate theoretically and experimentally highly tunable clamped–clamped microbeam resonators actuated with electrostatic forces. Theoretically, the Galerkin procedure is used to solve for static deflection as well as the eigenvalue problem as a function of the dc voltage for different values of the ratio between the air gap and the thickness of the microbeam. We demonstrate theoretically and experimentally that the natural frequency of the microbeam can increase or decrease with the increase of the dc polarization voltage depending on the ratio between the air gap and the thickness. Hence, we show that unlike the classical softening effect of the dc voltage, by careful designs of the microbeams, the dc bias can be used to effectively increase the resonance frequencies by several factors. Experimental data are presented for two case studies of silicon beams showing the effective increase of their fundamental resonance frequencies by more than 50–80%. Excellent agreement is reported among the theoretical and experimental results.
A Preliminary Design and Modeling Analysis of Two-Phase Volumetric Expanders for a Novel Reversible Organic Rankine-Based Cycle for Carnot Battery Technology

Carnot battery technology appears to be a promising solution to increase the development of power generation and offers a good solution for high-capacity, day-to-day energy storage. This technology may utilize the waste heat and store the electricity to recover it later. This article reports the preliminary analysis of a specially designed Carnot battery configuration employing a novel reversible Rankine-based thermodynamic cycle (RRTC). In this case, one volumetric expander is not only installed to generate power from a heat engine, but also to recover power during heat pump operating mode. The preliminary design and modeling results were obtained based on calculations taken from working fluid thermal properties of propane with some specific boundary conditions (i.e., secondary fluid hot temperature of 348.15 K, cooling temperature of 228.15 K, and waste heat temperature of 338.15 K). The results show that isentropic efficiency, pressure, and volumetric expansion ratio from both heat engine and heat pump operating modes are important parameters that must be taken into account when designing the two-phase expander for RRTC. The obtained results show that a designed two-phase volumetric expander in RRTC features a pressure ratio of 2.55 ± 1.15 and a volumetric ratio of 0.21 ± 0.105, and the Carnot battery may achieve the performance of 0.50–0.98.
Enhancing Ethanol Tolerance via the Mutational Breeding of Pichia terricola H5 to Improve the Flavor Profiles of Wine

Although using non-Saccharomyces yeasts during alcoholic fermentation can improve the wine aroma, most of them are not ethanol tolerant; therefore, in 2017, this study screened 85 non-Saccharomyces yeasts isolated and identified from 24 vineyards in seven Chinese wine-producing regions, obtaining Pichia terricola strain H5, which displayed 8% ethanol tolerance. Strain H5 was subjected to ultraviolet (UV) irradiation and diethyl sulfate (DES) mutagenesis treatment to obtain mutant strains with different fermentation characteristics from the parental H5. Compared with strain H5, the UV-irradiated strains, UV5 and UV8, showed significantly higher ethanol tolerance and fermentation capacity. Modified aroma profiles were also evident in the fermentation samples exposed to the mutants. Increased ethyl caprate, ethyl caprylate, and ethyl dodecanoate content were apparent in the UV5 samples, providing the wine with a distinctly floral, fruity, and spicy profile. Fermentation with strain UV8 produced a high ethyl acetate concentration, causing the wine to present a highly unpleasant odor. To a certain extent, UV irradiation improved the ethanol tolerance and fermentation ability of strain H5, changing the wine aroma profile. This study provides a theoretical basis for the industrial application of non-Saccharomyces yeasts that can improve wine flavor.
Lipase Activity, Hematological and Blood Biochemistry of Osphronemus gouramy Fed with Suplementation of Spirulina platensis and Chlorella vulgaris

Spirulina platensis and Chlorella vulgaris are algae that contain high nutrients, such as protein, vitamins, and minerals. The purpose of this study was to determine the lipase activity, hematological, blood biochemistry and to obtain the most effective supplementation of Spirulina platensis and Chlorella vulgaris in feed to enhance lipase activity, hematological parameter, blood biochemistry of gourami. The study was conducted experimentally in which 100 gourami fish were assigned randomely to the following treatments: P1 = Spirulina platensis 6 g kg-1 feed; P2 = Chlorella vulgaris 4 g kg-1; P3 = Spirulina platensis 3 g kg-1 + Chlorella vulgaris 2 g kg-1; P4 = Spirulina platensis 2 g kg-1 + Chlorella vulgaris 3 g kg-1; and C = feed without supplementation as control, in four replicates. Lipase activity was measured in various digestive organs at pH 2, 5, 7, 8 and 10. The results showed that supplementation of Spirulina platensis and Chlorella vulgaris affected lipase activity; hematological parameter and blood biochemistry of gourami. The combination Spirulina platensis + Chlorella vulgaris supplementation in feed showed the highest increased of the lipase activity, hematological parameter and blood biochemistry of gourami. Spirulina platensis + Chlorella vulgaris supplementation in feed might improve growth and immunity since the increase of digestive enzyme functioning which enhances feed utilization and the increase of biochemical parameters of blood, respectively.