An experiment was carried out to investigate the effect of different organic nutrient solutions and day of harvest on growth parameters, biomass and chemical composition of hydroponically grown sorghum red fodder. The experiment was a 3 × 2 factorial design comprising of 3 nutrient solutions (cattle, poultry and rabbit) and 2 harvesting regimes (8th and 10th day). Cattle, poultry and rabbit dungs were collected fresh and processed into nutrient solutions. Sorghum red seeds were treated, planted on trays, and irrigated twice per day with organic nutrient solution according to the treatments. Growth parameters which were investigated included fodder mat thickness, seedling height, leaf length and width, number of leaves, fresh and dry matter yield; and proximate composition. The results showed that sorghum red fodder irrigated with cattle manure nutrient solution (NS) harvested at 10 days was higher in all, except one (fodder mat thickness) of the growth parameters considered. The crude protein (CP) was highest and similar (P > 0.05) for Poultry NS harvested at 8 and 10 days, and Cattle NS at 10 days (13.13%, 12.67%, and 12.69% respectively). The ash content also favored Cattle NS at 10 days. Cattle NS at 10 days harvest was significantly (P < 0.05) the highest (7.00%), but comparable (P > 0.05) with Rabbit NS at 10 days for NDF. Fresh and DM yields were highest for Cattle harvested at 10 and 8 days respectively. The study recommends Cattle NS as hydroponic organic NS for sorghum red as it enhances fresh and dry matter yields, and nutritive values.

Background: Multiple sclerosis is often a longitudinal disease continuum with an initial relapsing-remitting phase (RRMS) and later secondary progression (SPMS). Most currently approved therapies are not sufficiently effective in SPMS. Early detection of SPMS conversion is therefore critical for therapy selection. Important decision-making tools may include testing of partial cognitive performance and magnetic resonance imaging (MRI). Aim of the work: To demonstrate the importance of cognitive testing and MRI for the prediction and detection of SPMS conversion. Elaboration of strategies for follow-up and therapy management in practice, especially in outpatient care. Material and methods: Review based on an unsystematic literature search. Results: Standardized cognitive testing can be helpful for early SPMS diagnosis and facilitate progression assessment. Annual use of sensitive screening tests such as Symbol Digit Modalities Test (SDMT) and Brief Visual Memory Test-Revised (BVMT-R) or the Brief International Cognitive Assessment for MS (BICAMS) test battery is recommended. Persistent inflammatory activity on MRI in the first three years of disease and the presence of cortical lesions are predictive of SPMS conversion. Standardized MRI monitoring for features of progressive MS can support clinically and neurocognitively based suspicion of SPMS. Discussion: Interdisciplinary care of MS patients by clinically skilled neurologists, supported by neuropsychological testing and MRI, has a high value for SPMS prediction and diagnosis. The latter allows early conversion to appropriate therapies, as SPMS requires different interventions than RRMS. After drug switching, clinical, neuropsychological, and imaging vigilance allows stringent monitoring for neuroinflammatory and degenerative activity as well as treatment complications.

The ways of developing functional textiles based on nanomaterials were introduced, and the latest research achievements of nanomaterials in such aspects as flame retardancy, antibacterial, super-hydrophobic, self-cleaning, UV resistance, and anti-static textiles were reviewed. The main technical obstacles to the large-scale application of nanomaterials in functional textiles were pointed out, the possible solutions were discussed, and the development of functional textiles by nanomaterials has been prospected.

The development of critical thinking (CT) enhances academic and professional opportunities. A review of literature reveals the use of fragmented analysis techniques, such as descriptive and correlational methods, among others, which hinder a deeper understanding of CT levels. This research aims to develop a methodology for analyzing Critical Thinking test scores, integrating five phases: exploratory, item analysis, scoring, gap analysis, and correlational. Using a quantitative approach, CT skills were analyzed with the Halpern Critical Thinking Assessment, which includes both open- and closed-ended questions to measure five skills: Verbal Reasoning (VR), Argument Analysis (AA), Hypothesis Testing (HT), Probability Use (PU), and Problem Solving (PS). The sample consisted of 214 students aged 18 and older. The item analysis phase categorized the items into quadrants: satisfactory, for review, or for elimination, based on difficulty and discrimination indices. The gap analysis revealed that Verbal Reasoning and open-ended formats were less satisfactory. The correlational phase, using heat maps, showed a stronger association between Verbal Reasoning and Probability Use. The methodological contributions include a variety of strategies that provide recommended procedures for analyzing tests or questionnaires in general. In today’s digital age, the development of critical thinking is not only a desirable skill but an essential necessity for the higher education system.

Modernizing the Internet of Things in Islamic boarding schools is essential to eliminate backwardness and skills gaps. Santri must have cognitive, affective, psychomotor, and creative intelligence to be ready to enter the industrial and business world. The students’ need for information transparency can be resolved using technology. This is because the empowerment of the Internet of Things has become a separate part of Islamic boarding school activities with students who can connect in real-time. This research aims to analyze current conditions and stakeholder involvement regarding the application of the Internet of Things in innovative Islamic boarding school services in the era of disruption. The Descriptive Method and Individual Interest Matrix Analysis were used by involving 130 respondents from the internal environment of the Daarul Rahman Islamic boarding school and completing the questionnaire through FGD (Focus Group Discussion) with the leaders of the Daarul Rahman Islamic boarding school. The results show that the current condition of Islamic boarding schools is that most need to learn or understand IoT, even though they are enthusiastic about learning new things and flexible in accepting change. The challenges required in implementing IoT are financial investment, increasing human resources through training, and synergy between Islamic boarding school policy makers. Mutually supportive and solid conditions are required between foundations, school principals, and school committees to implement IoT at Daarul Rahman Islamic Boarding School. Collaboration with various parties is needed because the implementation of IoT cannot be done alone by Islamic boarding schools but with the support of various related parties.

This study introduces a novel Groundwater Flooding Risk Assessment (GFRA) model to evaluate risks associated with groundwater flooding (GF), a globally significant hazard often overshadowed by surface water flooding. GFRA utilizes a conditional probability function considering critical factors, including topography, ground slope, and land use-recharge to generate a risk assessment map. Additionally, the study evaluates the return period of GF events (GFRP) by fitting annual maxima of groundwater levels to probability distribution functions (PDFs). Approximately 57% of the pilot area falls within high and critical GF risk categories, encompassing residential and recreational areas. Urban sectors in the north and east, containing private buildings, public centers, and industrial structures, exhibit high risk, while developing areas and agricultural lands show low to moderate risk. This serves as an early warning for urban development policies. The Generalized Extreme Value (GEV) distribution effectively captures groundwater level fluctuations. According to the GFRP model, about 21% of the area, predominantly in the city’s northeast, has over 50% probability of GF exceedance (1 to 2-year return period). Urban outskirts show higher return values (> 10 years). The model’s predictions align with recorded flood events (90% correspondence). This approach offers valuable insights into GF threats for vulnerable locations and aids proactive planning and management to enhance urban resilience and sustainability.