Indonesia’s stock market has seen an increase in investment due to the ease of investing and the availability of information about stocks on different social media platforms. This research uses a social network approach to analyze overconfidence behavior in millennial stock investors. This research uses a descriptive quantitative method. The population used in this study are capital market investors in the Greater Solo area who are millennials (<30 years). The number of stock investors in the Greater Solo area is 60,542 investors. The sampling technique in this study was non-probability sampling using purposive sampling. This research uses the AMOS SEM (Structural Equation Model) analysis tool. The conclusion of this study is that millennial investors’ overconfidence behavior increases influenced by financial literacy. investor skills. family ties and friendship ties. The contribution of this research can be applied to understand and educate millennial investors in order to overcome overconfidence behavior so that they can anticipate the losses received. This research may have implications for improving Behavioral Finance Integration Incorporating insights from behavioral finance into investment strategies can help mitigate the negative effects of overconfidence. The limitation in this study is that the scope used in the study is only in the greater solo area.

Studies show that the COVID-19 crisis may threaten to attain sustainable development goals connected with shelter in developing countries, including Malaysia. Low-cost housing provision has been identified as one tool for achieving sustainability goals via synergistic operations. However, studies about post-COVID-19 housing and sustainable development goals integration are scarce in Malaysia. The study investigated the state of post-COVID-19 housing and developed a framework to integrate Goals in housing provision in Malaysia. The study covered four major cities in Malaysia via qualitative research to achieve the study’s objectives. The researchers engaged forty participants via semi-structured virtual interviews, and saturation was achieved. The study utilized a thematic analysis for the collated data and honed them with secondary sources. Findings show that COVID-19 reduced the possibility of low-income earners becoming homeowners. This is because the low-income groups were real losers of COVID-19 economic changes. Also, findings reveal that achieving four Goals from the 17 Goals will improve housing provision in Malaysia’s post-COVID-19 era. The study encourages key housing stakeholders to improve housing delivery, especially for the low-income earners across Malaysia in the post-COVID-19 era. This will imply contributing to achieving four Goals because of the correlation, as part of the study’s implications.

A three-factor experiment was set at the Horticulture Laboratory, Hajee Mohammad Danesh Science and Technology University, Dinajpur, to study the effects of the controlled deterioration (CD) on the pea seeds at the constant temperature of 35 ℃. The 3 factors considered were: 3 pea seed sources (Rangpur Local/RL, Dinajpur Local/DL and Thakurgaon Local/TL); 3 ageing periods (0, 8 and 16 days); and 3 seed moisture contents (12, 16 and 20% MC). The 27 treatment combinations compared in the CRD with the 3 repetitions for the 8 arenas were: % germination, % abnormal seedlings, % dead seeds, % soil emergence and seedling evaluation test for the root and shoot lengths as well as their dry matter contents. Identical prototypes of notable (5–1% level) degradations were recorded everywhere. But the disparities were lucid under the extreme stresses. Moreover, highly noteworthy (1% level) relations were traced amid all the traits ranging from -0.9847 (soil emergence × abnormal seedling) to 0.9623 (soil emergence × normal seedling). So, the CD technique was very effectual in judging the physiological statuses of the seed sources studied. Thus, the germination test might be add-on by a vigor test, the latter of which could be assessed by quantifying the seedlings’ root and shoot lengths and/or their dry matter accumulations. Moreover, in the seed quality certification, the suitable limits of vigor for the chosen traits could also be got by this technique. But the seeds of several pea varieties should be exploited to fix-up the agreeable limits of the traits. Furthermore, to save time, the ageing period could be squeezed by raising the seed MC.

Land use changes have been demonstrated to exert a significant influence on urban planning and sustainable development, particularly in regions undergoing rapid urbanization. Tehran Province, as the political and economic capital of Iran, has undergone substantial growth in recent decades. The present study employs sophisticated Geographic Information System (GIS) instruments and the Google Earth Engine (GEE) platform to comprehensively track and analyze land use change over the past two decades. A comprehensive analysis of Landsat images of the Tehran metropolitan area from 2003 to 2023 has yielded significant insights into the patterns of land use change. The methodology encompasses the utilization of GIS, GEE, and TerrSet techniques for image classification, accuracy assessment, and change detection. The Kappa coefficients for the maps obtained for 2016 and 2023 were 0.82 and 0.87 for four classes: built-up, vegetation cover, barren land, and water bodies. The findings suggest that, over the past two decades, Tehran Province has undergone a substantial decline in ecological and vegetative areas, amounting to 2.4% (458.3 km²). Concurrently, the urban area and the barren lands have expanded by 287.5 and 125.5 km², respectively. The increase in water bodies during this period is likely attributable to the reduction of vegetation cover and dam construction in the region. The present study demonstrates that remote sensing and GIS are excellent tools for monitoring environmental and sustainable urban development in areas experiencing rapid urbanization and land use changes.

This work aimed to evaluate the effects of using three different substrates in the semi-hydroponic culture of lettuce (Lactuca sativa L.) using two different nutrient solutions. A first trial was performed with a nutrient solution rich in macronutrients and micronutrients suitable for lettuce culture, and a second trial with a nutrient solution with pretreated wastewater from effluents of a cheese factory. The experimental design was in randomized blocks with three repetitions and three substrates were used: perlite, coconut fiber, and expanded clay, in both trials. The following parameters were observed: number of leaves, diameter of the cabbage, fresh and dry weight of the aerial part, chlorophyll index and mineral composition of the lettuce. For the first trial, the highest result for the number of leaves (20 leaves), fresh weight (142.0 g) and dry weight (7.2 g) of the aerial part was obtained in the plants growing on perlite. In the second trial, the highest result for the number of leaves (28 leaves), diameter of cabbage (26.7 cm), fresh weight (118.8 g) and dry weight (9.5 g) of the aerial part were achieved by the plants that were grown in coconut fiber. The nutrient solutions were analyzed after each irrigation cycle to verify the possibility of their discharge into the environment. Several parameters were analyzed: pH, conductivity, redox potential, nitrates, nitrites, ammoniacal nitrogen, chlorides, hardness, calcium, phosphates, sodium, potassium, chemical oxygen demand (COD) and magnesium. Ammoniacal nitrogen was found to be the only nutrient that can limits the discharge of nutrient solutions into the environment. It was also proven that the plants, besides obtaining the nutrients necessary for their development in the semi-hydroponic system with the nutrient solution with pre-treated residual water, also functioned as a purification system, allowing the said nutrient solution to be discharged into the environment at the end of each cycle.

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.