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Researching rapid multiplication techniques for mosaic-resistant cassava in tunnel greenhouses is crucial for ensuring food security and sustainable agriculture. Our previous findings indicated that a combination of 50% shading and 70-75% humidity significantly enhanced the formation of shoots and growth of cassava seedlings in a tunnel greenhouse. The current study examines the impact of different substrate compositions on cassava propagation. The experiments were designed as split plots with three replicates and four formulas including CTRL: 100% sand with a thickness of 40 cm; CT-1: 100% sand with a thickness of 30 cm; CT-2: 60% sand and 40% gravel with a thickness of 40 cm; CT-3: 70% sand and 30% gravel with a thickness of 40 cm; and CT-4: 50% sand and 50% gravel with a thickness of 40 cm. The results demonstrated that CT-3 yielded the highest shoot formation rate and growth of cassava seedlings, suggesting that the combination of sand (70%) and gravel (30%) at a thickness of 40 cm provide the most favorable conditions for cassava propagation in tunnel greenhouse conditions.

Analogical thinking is a crucial strategy for mathematical problem-solving, enabling the discovery of solutions by identifying similarities between different problems. However, existing research needs a comprehensive classification of students' use of analogical thinking in this context. This study aims to develop a new classification framework for analogical thinking in mathematical problem-solving, emphasizing the identification and utilization of analogous methods between source and target problems. The research adopts a descriptive qualitative approach involving a purposive sample of 15 high school students from Surakarta, Central Java, who demonstrated analogical thinking in solving both source and target problems. Data collection was conducted through tests, observations, and interviews, with analysis performed using the constant comparative procedure (CCP). The findings reveal three distinct classifications of analogical thinking: pattern recognition (identifying common patterns to solve both source and target problems), variable utilization (using variables as symbolic tools for problem-solving), and visualization (applying graphical representations to address the issues). This study offers significant theoretical insights for future research and practical implications for applying analogical thinking in enhancing mathematical problem-solving.

This research investigates the impact of drought and waterlogging stresses on the morphological and physiological characteristics of black pepper (Piper nigrum). The greenhouse experiment was laid out in a Randomized Complete Block Design (RCBD) with treatments consisting of three water regimes (drought, control, and waterlogging), all replicated three times. The results suggested that the root traits of black pepper, such as root length and surface area, showed considerable reductions under both stress conditions, with more severe impacts observed under waterlogging. The significant reductions were observed in plant height, number of leaves, number of branches, leaf area, and SPAD value, root and shoot dry weight of black pepper. Gas exchange parameters also decreased markedly under drought stress, with waterlogging causing an even greater reduction. The findings provide valuable insights into managing the effects of environmental fluctuations on black pepper cultivation.

Accurately predicting the compressive strength of foamed concrete plays a key role in the wide application of foamed concrete in practice. This study investigates the performance of the six AI models in estimating the compressive strength of foamed concrete. A dataset of 150 samples available in the literature was used for training and testing the AI models. The dry density, cement and sand content, and water-to-cement ratio were employed as input parameters, while the 28-day compressive strength was used as the output parameter. Four statistical indicators were utilized to evaluate the performance of the AI models. The study results reveal that the AI models yield an accurate prediction of the compressive strength of foamed concrete. The best performance model in estimating the compressive strength of foamed concrete is the M5Rules model, while the least accurate model depends on the indicators used to measure the accuracy of the AI models.

Purpose: Co-composting of mango by-products and biogas solid residue eliminates some shortcomings of composting these wastes separately. Specifically, co-composing solves the problem of the low pH values in mango by-products while enhances biodegradable organic matter of biogas solid residues. However, no research report is available on co-composting of mango by-products (MB) and biogas solid residue (BR). Method: This study established three in-vessel lab-scale composting bins with 3 different C/N ratios, including Bin 1: 27.4/1 (156 kg MB + 144 kg BR); Bin 2: 30.23/1 (193 kg MB + 107 kg BR); and Bin 3: 37.7/1 (224 kg MB + 76 kg BR). The raw compost materials underwent 57 days of incubation, including 36 days of raw incubation and 21 days of mineralization. Results: Bin 3 containing larger amounts of mango by-products and less amounts of biogas residue showed a higher percentage of remaining carbon in the final products (17.97%), lower nitrogen loss (17%), and showed 0.5% increase in available P2O5 content, compared to the other bins. From 300 kg of initial raw material, the final compost mass in Bin 1, Bin 2, and Bin 3 were 26.2 kg, 32.7 kg, and 88.1 kg, respectively. Conclusion: Resultantly, an initial C/N ratio of 37.7/1 could be suggested in the aerobic co-composting of biogas residue with mango by-products. Research Highlights · Co-composting of mango by-products and biogas solid residue eliminates some of the weaknesses of composting these wastes separately. · The incubation period determined was 57 days of incubation, including 36 days of raw incubation and 21 days of mineralization. · Among three C/N ratios surveyed, the highest C/N in bin 3 (C/N=37.7/1) showed the best-favoured condition for mango by-products treatment and generate the highest amount of compost product. · Bin 3 showed the highest percentage of remaining carbon in compost products (17.97%), a lower in nitrogen loss (17%), and 0.5% increase in available P2O5 content.

The Phan Rang sheep, considered the sole indigenous breed of Vietnam, are primarily concentrated in the two central provinces of Ninh Thuan and Binh Thuan, with Ninh Thuan accounting for more than 90% of the country’s sheep population. These provinces are known for their high temperatures and frequent droughts. The long-standing presence of the Phan Rang sheep in these regions suggests their potential resilience to heat stress—a trait of increasing interest in the face of global climate change. Despite the breed’s significance, a critical knowledge gap hinders conservation and breeding programs. To address this, our study employed a two-pronged approach. First, we collected body conformational data to aid in breed identification. Second, we analyzed mitochondrial DNA (D-loop) and Y chromosome markers (SRY and SRYM18) to elucidate the maternal and paternal lineages. Among the 68 Phan Rang sheep analyzed for their D-loop, 19 belonged to mitochondrial haplogroup A, while 49 belonged to haplogroup B. The haplogroups can be subdivided into 16 unique haplotypes. All 19 rams surveyed for their paternal lineages belonged to haplotypes H5 and H6. These findings strongly support the hypothesis of dual origins for the Phan Rang sheep. This study presents the first genetic data for the Phan Rang breed, providing crucial insights for future research and conservation efforts.

The main aim of this study is to investigate the relationship between strategists’ intuitive and analytical thinking, innovation, and corporate competitive advantage. This study not only proposes the new model to the academic world but also provides the empirical investigation on the direct and indirect effect of a strategist’s analytic reasoning perspective and strategist’s generative reasoning perspective on innovation and competitive advantage as well as the mediating role of innovation between the strategist’s cognitive perspective of reasoning and corporate competitive advantage. This study conducted questionnaires of 382 samples in state-owned companies, FDI, and private companies in Vietnam. Structure equation modelling was applied through smart PLS to analyse the valid data. The results provide substantial evidence of significant relationships between strategists’ cognitive perspectives of reasoning, innovation, and competitive advantage in the context of State own, FDI, and private companies in Vietnam. Besides, the findings also show that there are non-relationships in the direct effect between product innovation and competitive advantage and between marketing innovation and competitive advantage. Moreover, the research results imply various managerial implications regarding how organizations successfully increase their competitive advantage by increasing their leader’s cognition in management.

Drying plays an important process for wastewater sludge management, as it can minimise the volume of wastewater sludge before disposal, and consequently the cost of storage, handling and transport. In this study, the wastewater sludge was dried by using a solar tunnel greenhouse drying system. The performance of the dryer for drying wastewater sludge has been analyzed through no load and full load test. The three full load drying tests recorded that the temperature inside the tunnel dryer fluctuated around 55±5°C; while the no load drying test, the temperature of the drying tunnel maintained within 60±5°C; as compared to the ambient temperature of 30±5°C. The average moisture content of solar dried sludge decreased from 88.69 - 90.84% to 7.78 – 13.30% in the mixing conditions and 14.78 – 19.52% in the non-mixing conditions, in 5 days. The study suggests that the semi-cylindrical solar tunnel dryer of wastewater sludge has given satisfactory results within five days.

PurposeTo examine the effects of volume and method on fluorescein tear breakup time (TBUT) values and to evaluate test efficacy in an independent sample free of selection bias.MethodsSubjects were assessed using a battery of dry eye tests (DETs). Efficacy study: Subjects were randomized to the DET, standard strip, and liquid NaFl on separate days. A masked examiner measured TBUTs from video recordings. Verification study: Subjects were investigated for efficacy using volumes of 5.0 and 2.0 μL mL of NaFl for TBUT.ResultsEfficacy study: 46 subjects completed the study. Log-transformed TBUTs were significantly different, normal subjects versus dry subjects, for all 3 methods (all P values < 0.001). Area under the curves (AUCs), cut-points, sensitivity, and specificity were 1) DET: 0.873, 4.4 seconds, 0.97, and 0.67, respectively; 2) 2.0 mL: 0.901, 3.22 seconds, 0.90, and 0.87, respectively; and 3) standard strip: 0.912, 3.42 seconds, 0.97, and 0.80, respectively. Verification study: Data splitting analysis for the 2.0 μL data (n = 174 dry subjects and 97 normal subjects) generated an AUC of 0.917 and a cut-point of 6.05 seconds for a sensitivity of 0.87 and a specificity of 0.81. The 5.0 μL sample yielded an AUC of 0.940, with a sensitivity and specificity of 0.92 and 0.83, respectively, at a cut-point of 5.5 seconds.ConclusionsLittle difference in TBUT was found using the 3 clinical methods with video recordings. Analysis using liquid NaFl suggests that the TBUT test has excellent diagnostic accuracy and that a cut-point of 5.3 to 6.0 seconds is the optimum to differentiate normals from persons with dry eye.

U Minh Thuong National Park is a key site for wetland biodiversity conservation in Vietnamese Mekong Delta. This paper outlines a field experiment carried out in U Minh Thuong National Park in the dry season 2019. The study aimed to compare methane emissions and related physicochemical soil and water parameters between the Peat swamp forest and Melaleuca forest. The results show that both water and soil parameters at 8 examined sites in Melaleuca forest and Peat swamp forest fluctuated highly over the sampling intervals. The average hourly C-CH4 emission rates in Melaleuca forest (26.58 Eg/m2/h) was higher than that in Peat swamp forest (21.18 Eg/m2/h). Generally, water level and redox potential were important factors regulating emissions of methane gases. The Eh values were all negative values, ranged between ∁E96.5 ± 22.75 EV and ∁E7.75 ± 15.37 EV, indicative of high electron activity and intense anaerobic. Peat swamp forest’s soil had relatively higher organic matter, CEC, TN and TP values than Melaleuca forest’s soil. The COD values fluctuated between 197.3 ± 51.78 Eg/L and 396.8 ± 25.77 Eg/L, indicative of organic pollution of surface water. It is suggested shorter time measurement (at least twice a day) of methane emission for more accurate evaluation.

In this study, the shrimp shell-derived chitosan was coated onto rice husk-derived biochar to form chitosan/biochar bio-composite beads. The physicochemical properties of biochar (BC) and chitosan/biochar beads (CS@BC) were characterized by BET, SEM-EDX, FTIR, and pHpzc analyses, which were then tested for their capacity to remove Safranin O (SO) from water. In kinetics, the pseudo-second-order model was found to well represent experimental data, indicating the adsorption was mainly a chemical process. The intra-particle diffusion model was not the sole rate-limiting step, because the results did not pass through the origin. In isotherms, both the Langmuir and Freundlich models described well the equilibrium adsorption data. The CS@BC adsorbent showed adsorption capacity at 77.94 mg/g for SO, which is higher than BC adsorbent with 62.25 mg/g (experimental conditions: pH ~ 7.0, dosage = 0.2g, contact time = 240 min, and temperature = 298K). The findings revealed that the biochar-loaded chitosan can improve the adsorption capacity of SO. It is predicted that the enhancement in the functional groups (i.e., -NH2 and -OH groups) of CS@BC could contribute to the electrostatic interactions and the complexation between SO and CS@BC, thereby enhancing the Safranin O adsorption from water.

How to choose the most appropriate courses to study throughout the learning process remains a question interested in by many students. Students often choose suitable courses according to their interests, needs, and advice from supporting staff, etc. This paper presents the results in developing a course recommendation system that will select appropriate courses for each student studying a major in the following semesters based on his/her current academic performance. We have applied several techniques based on data mining and learning analytics to predict students' learning outcomes in the next semester and developed a model to select the appropriate courses based on such a recommendation system. Besides, our study has focused on comparing the effectiveness of predictive learning methods based on collaborative filtering. Experiments analyzed the learning results of 510 students who enrolled in the courses from 2015 to 2019 and showed that the Matrix Factorization method is the most effective. Also, the paper has proposed procedures and constraints applicable to different training curricula.

PurposeThis study examined whether hyperspectral stimulated Raman scattering (hsSRS) microscopy can detect differences in meibum lipid to protein composition of normal and evaporative dry eye subjects with meibomian gland dysfunction.MethodsSubjects were evaluated for tear breakup time (TBUT), staining, meibum expression and gland dropout. Expressed meibum was analyzed using SRS vibrational signatures in the CH stretching region (2800-3050 cm-1). Vertex component analysis and K-means clustering were used to group the spectral signatures into four fractions containing high lipid (G1) to high protein (G4).ResultsThirty-three subjects could be statistically analyzed using pooled meibum (13 with stable tear films (TBUTs > 10 s) and 20 with unstable tear films (TBUTs ≤ 10 s). Significant differences in meibum from subjects with unstable vs. stable TBUTs were found for the G1 fraction (medians 0.164 and 0.020, respectively; p = 0.012) and the G2 fraction (medians 0.244 and 0.272, respectively; p = 0.045). No differences were observed for the G3 and G4 fractions. Single orifice samples were not significantly different vs. pooled samples from the fellow eye, and eyelid sector samples (nasal, central and temporal) G2:G3 fractional components were not significantly different (p = 0.449). Spearman analysis suggested a significant inverse correlation between G1 fraction and TBUT (R = -0.351; p = 0.045).ConclusionshsSRS microscopy allows compositional analysis of expressed meibum from humans which correlated to changes in TBUT. These findings support the hypothesis that hsSRS may be useful in classifying meibum quality and evaluating the effects of therapy.