The present study was carried out to investigate the phytochemical and antimicrobial activity of leaves of the plant Henckelia humboldtiana. H. humboldtiana is a member of the Gesneriaceae family and comprises medium-sized plants belonging to the order Lamiales. Secondary metabolites are produced by plants as their response to various extrinsic and intrinsic factors. Compared to primary metabolites plants produce secondary metabolites in smaller quantities. This species is known to contain a diverse range of bioactive compounds, including tannins, flavonoids, and terpenes, which contribute to its various biological and pharmacological activities. Characterization of metabolites using a single analytical technique is often inadequate. Therefore, a combination of experimental approaches and multiple instrumental platforms is required for comprehensive analysis of the phytoconstituents present in plant extracts. In this study, the methanolic and hexane leaf extracts of the plant were subjected to phytochemical analysis using chromatographic techniques such as High-Performance Thin Layer Chromatography (HPTLC) and Gas Chromatography–Mass Spectrometry (GC–MS). Major compounds obtained from methanol extract of leaves include caryophyllene, neophytadiene, trans-cinnamic acid, neointermedeol and hexane extract of leaves include dodecane, ylangene, caryophyllene, humulene. Plant extract exhibit antimicrobial effect on diffusion method.

This article summarizes the main findings of the author's reconstruction of Leningrad's pre-war industry (June 1940 – June 1941) conducted between 2016 and 2025. Using direct counting, the number and geographic location of all industrial enterprises, including industrial cooperatives, within the city's administrative boundaries in the pre-war year were determined. The product range was identified, and the people's commissariats and departments to which Leningrad industrial enterprises were subordinate were established. Enterprises are grouped according to their subordination, and the personnel numbers of most large and medium-sized plants and factories are ascertained. Civilian enterprises with military order programs in the pre-war period were identified, and the minimum estimated number of Leningrad manufacturers fulfilling defense orders in the pre-war year was determined. The sectoral structure of Leningrad industry is presented, enterprises are ranked by social significance, from "large" to "small," and biographical particulars are collected for the managers of large, medium, and some small enterprises (directors, party organizers/secretaries of the All-Union Communist Party (Bolsheviks), and chief engineers). The structured dataset is defined as a "model of Leningrad industry". The model's application opens up broad possibilities for studying processes and conditions both within the given time period and beyond. The model is scalable (its information capacity is unlimited), has an open architecture (it can be expanded with new criteria), and enables research over time periods extending beyond the initially defined framework

This study applies the Flash Pressurized Flotation (FPF) process, which generates stable and uniform microbubbles under low-pressure conditions without a high-pressure saturator, and comparatively evaluates its treatment efficiency and energy-saving performance against the conventional Dissolved Air Flotation (DAF) process from a Best Available Technology (BAT) perspective. The bubble generation characteristics of the FPF process were quantitatively analyzed by evaluating the effects of major operational parameters, including the number of orifices, number of plates, nozzle configuration, flow rate, and pressure. Experiments were conducted using synthetic lake water, where bubble size was measured by the Particle Counter Method (PCM) and bubble volume was determined by the Water Substitution Method. Increasing the number of orifices from 5 to 15 reduced the average bubble size from 4.3 μm to 4.1 μm and increased the bubble volume from 1.1 mL/L to 1.5 mL/L. Under a flow rate of 2.04 L/min and a pressure of 2 atm, the FPF process showed relatively superior bubble generation characteristics with an average bubble size of 26 μm and a bubble volume of 60 mL/L, while the FPF-type dual-plate nozzle exhibited the best performance, producing an average bubble size of 31.5 μm and a bubble volume of 51 mL/L. Compared with the DAF process at the same pressure, the FPF process achieved higher removal efficiencies for phosphorus (94.1%) and turbidity (89.9%), whereas the DAF process showed removal efficiencies of 30.1% and 33.1%, respectively. The specific energy consumption of the FPF process was 0.0024 kWh/m³, representing an approximately 98% reduction compared to that of the DAF process, demonstrating the potential of FPF as a low-energy flotation process suitable for small- and medium-sized water treatment plants and as a BAT.

With the advent of the Industry 4.0 era, the manufacturing industry is implementing a range of novel technologies on the factory floor, leading to the generation of substantial quantities of production data. However, the development of analytics tools capable of processing these data and extracting valuable information for decision-making and production control lags behind. In addition, a noticeable amount of raw data collected from the factory floor is prone to errors, especially in small- and medium-sized manufacturing plants, and their processing often requires a laborious data cleaning process due to the limitations of the sensors and the noisy environment of the manufacturing facilities. This presents a challenge in utilizing factory floor production data effectively. This paper addresses the challenge by focusing on the parts flow data, which reflects the number of parts in each buffer as a function of time in a production system. In particular, we study the parts flow data in discrete-time serial production line models, assuming that the data are subject to random noise, and develop effective and robust algorithms that can effectively detect and correct errors in these data. To improve the computational efficiency for complex cases (longer lines, higher error rates, etc.), a decomposition-based approach is used to parallelize the computation procedure at implementation. Numerical experiments demonstrate that the proposed methods can enhance data quality by more than 40% and improve the accuracy of system performance metrics estimation by over 50% using corrected data. These improvements can facilitate more reliable process monitoring and production control in manufacturing environments.

The emissions from biomass combustion systems have recently been the subject of increased attention. In addition to elevated concentrations of particulate matter and hydrocarbons (HCs) in the flue gas, significant levels of NOx emissions occur depending on the used fuel, such as biogenic residues. In response to legal requirements, owners of medium-sized plants (≈100 kW) are now also forced to minimize these emissions by means of selective catalytic reduction systems (SCR). The implementation of a selective sensor is essential for the efficient dosing of the reducing agent, which is converted to ammonia (NH3) in the flue gas. Preliminary laboratory investigations on a capacitive NH3 sensor based on a zeolite functional film have demonstrated a high sensitivity to ammonia with minimal cross-influences from H2O and NOx. Further investigations concern the application of this sensor in the real flue gas of an ordinary wood-burning stove and of combustion plants for biogenic residues with an ammonia dosage. The findings demonstrate a high degree of agreement between the NH3 concentration measured by the sensor and an FTIR spectrometer. Furthermore, the investigation of the long-term stability of the sensor and the poisoning effects of SO2 and HCl are of particular relevance to the laboratory measurements in this study, which show promising results.

Rovno and Baltic amber inclusions are known as a rich source of late Eocene mosses. Most of them are either referred to extant genera or placed in form-genera with names meaning similatity to an extant taxon. The present moss from Rovno amber is rather exceptional, having combination of features different from any extant mosses known for us. Therefore it is described as Rovnohypnum gen. nov., characterized by medium-sized plants, non-branched shoots that are attenuate to their tips, moderately loosely foliate, leaves spreading, ovate, acuminate, cordate at base, costa double, cells elongate, with one to three prominent papillae on dorsal surface, smooth or much weaker papillose on ventral side, proximal branch leaves subdivided into subfilamentose lobes. Putative brood filaments are noticed in many leaf axils. We compare this moss with the Pylaisiadelphaceae, where the brood filaments, pluripapillose cells, and filamentose or subfilamentose structures surround the branch primordia. However, these traits are characteristic for different genera of the family, thus we refer it in a new genus within the Pylaisiadelphaceae.

Cement production is a carbon-intensive process that contributes significantly to global greenhouse gas emissions. Approximately 50–60% of these emissions result from limestone calcination, while 30–40% result from fossil fuel combustion in kilns. This study presents a multi-objective optimization (MOO) framework that integrates raw mix design and alternative fuel blending to simultaneously reduce production costs and carbon dioxide (CO2) emissions while maintaining clinker quality. A hybrid Genetic Algorithm–Linear Programming (GA-LP) model was developed to navigate the balance between economic and environmental objectives under stringent chemical and operational constraints. The approach models the impact of raw materials and fuel ash on critical clinker quality indices: the Lime Saturation Factor (LSF), Silica Modulus (SM), and Alumina Modulus (AM). It incorporates practical constraints such as maximum substitution rates and specific fuel compositions. A case study inspired by a medium-sized African cement plant demonstrates the utility of the model. The results reveal a Pareto front of optimal solutions, highlighting that a 20% reduction in CO2 emissions from 928 to 740 kg/ton clinker is achievable with only a 24% cost increase. Optimal strategies include 10% fly ash and 30–50% alternative fuels, such as biomass, tire-derived fuel (TDF), and dynamic raw mix adjustments based on fuel ash contributions. Sensitivity analysis further illustrates how biomass cost and LSF targets affect clinker performance, emissions, and fuel shares. The GA-LP hybrid model is validated through process simulation and benchmarked against African case studies. Overall, the findings provide cement producers and policymakers with a robust decision-support tool to evaluate and adopt sustainable production strategies aligned with net-zero targets and emerging carbon regulations.

Urban plant care is increasingly important amid growing concerns about air pollution and limited time for manual maintenance. In Indonesia, air quality has deteriorated significantly, with PM2.5 pollution levels exceeding World Health Organization standards, particularly in major cities like Jakarta. Ornamental plants play a crucial role in improving air quality; however, urban residents often struggle to consistently water them. This study addresses that problem by developing an Internet of Things (IoT)-based smart irrigation system that utilizes the Sugeno fuzzy algorithm to predict the water needs of ornamental plants. The system combines a capacitive soil moisture sensor and a DHT11 temperature-humidity sensor with an ESP8266 microcontroller to monitor environmental conditions. Data is transmitted to Firebase and visualized in an Android application, which provides real-time monitoring and specific volume recommendations ranging from 10 ml to 240 ml, calibrated for medium-sized plant pots which is also based on 27 fuzzy rules derived from three input parameters: air temperature, humidity, and soil moisture. Real-world testing with the Aglaonema Snow White plant confirmed that the system functions reliably, helping users optimize water usage and support sustainable, data-driven plant care in urban environments. The system achieved an average prediction accuracy of 89.14% and a mean absolute error of 7.6% in guiding soil moisture toward a 70% target, confirming its practical effectiveness. While the system was tested on Aglaonema Snow White, the fuzzy rule base can be recalibrated for other ornamental plant species with different water needs.

The plant Ventilago maderaspatana belongs to the genus Ventilago, within the family Rhamnaceae. It’s commonly known as the “Red Creeper” and in Tamil as “Surulbattaikkoti”. It is a medium-sized plant. Panicles axillary and terminal, to 15 cm long, grey pubescent; pedicels to 3 mm, pubescent; calyx tube obconic, 1 mm, lobes to 2 mm, triangular; petals 1 mm, obovate; stamens 5, opposite to the petals, filaments 1 mm, disc flattened, 5-angled; ovary half inferior, pubescent, style 0.5 mm, stigma shortly bifid. Different qualitative tests for alkaloids, catechin, coumarin, glucoside, flavonoids, saponins, fixed oils, terpenoids, phenols, steroids, anthroquinones, quinines, xanthoprotein and sugar. It exhibits effective pharmacological activity, including antimicrobial, antidiabetic, anti-inflammatory, antibacterial, hepatoprotective, cardioprotective, antihyperlipidemic, antiulcer, antioxidant, and anticancer properties [1]. It contains crucial medical constituent compounds, such as Anthraquinone derivatives Ventinone A and B, chrysophyll, emodine, and islandicin—naphthalene derivatives of naphthalene and maderona. Fruits contain lupeol and sitosterol. Leaf and stem contain their glycosides. Stem bark contains friedelin. The results from this review are quite promising for the use of Ventilago madraspatana, a multipurpose medicinal agent, which has been successfully utilised in Siddha medicine in various countries. More clinical trials should be conducted to support its therapeutic use [2].

The ways to achieve the requirements of modern environmental legislation of Ukraine and the European Union regarding the limiting emissions of pollutants from large and medium-sized combustion plants concerning the solid fuel steam boilers of municipal and industrial combine heat and power plants (CHPP) in Ukraine is analyzed in the paper. The environmental requirements and technologies for cleaning flue gases of solid fuel boilers from the main pollutants, namely particulate matter, sulfur dioxide and nitrogen oxides, were considered, and the effectiveness, advantages and limitations for the implementation of these technologies on existing boilers of thermal power plants were analyzed. The existing state of gas cleaning equipment, put into operation more than fifty years ago, does not meet current environmental requirements, and the urgent issue is the reconstruction and modernization of existing and the construction of new gas cleaning plants. The use of fabric filters, electrostatic filters and wet scrubbers with a Venturi tube will allow to fulfill the requirements of European directives on dust emission limit values, and the most rational solution will be to use the existing wet scrubbers with a Venturi tube, which are equipped on the vast majority of CHPPs, by significantly increasing the specific flow rate of liquid for irrigation. For the capture of gaseous pollutants, a promising direction is the use of ammonium reagents for highly efficient desulfurization and obtaining ammonium sulfate as a desulfurization product, which is a mineral fertilizer, and the reduction of nitrogen oxides to molecular nitrogen. The use of an aqueous solution of ammonia in a wet scrubber with a Venturi tube will allow to simultaneously capture fly ash and sulfur dioxide in one device. To reduce nitrogen oxide emissions in CHPP boilers, it is advisable from the point of view of investment costs and spatial conditions to use the method of selective non-catalytic reduction.

This paper presents the results of research on metal migration from the biochar-amended soil to plants with edible root – radish (Raphanus sativus, Saxa 2), and edible above-ground part – butterhead lettuce (Lactuca sativa, Queen of May). The soil was enriched with biochar obtained from municipal sewage sludge through pyrolysis at 750–850°C in a pilot container installation designed for small – and medium-sized sewage treatment plants in agglomerations up to 10,000 population equivalents. The obtained biochar was characterised by a high content of sodium, magnesium, aluminium, potassium, calcium, and iron. The pot experiment was conducted under laboratory conditions at a constant temperature of 22°C, with humidity ranging from 39% to 55%. An additional light source was used to ensure optimal conditions for plant development, emitting light that simulated the insolation conditions typical of the growing season at Poland’s latitude. The vegetables were watered three times a week. The leachability test showed that elements were strongly bound to the biochar material and migrated to the aquatic environment in trace amounts. The influence of 5%, 10%, and 15% biochar addition to the soil substrate on vegetable growth and metal content was studied. A positive effect of biochar addition on vegetable yields was observed; the highest biomass of radish and lettuce was obtained in the substrate containing 5% biochar, where the yield increased by 6% and 17%, respectively. It was also observed that the addition of 5% biochar reduced metal concentrations in vegetables compared to the control. The determined content of heavy metals (lead and cadmium) in vegetables did not exceed the permissible levels specified by EU regulations. The high temperature of 750–850°C in the pyrolysis reactor allows for effective sanitation of municipal sewage sludge, resulting in a carbon material that can be successfully used in agriculture to improve soil properties. The use of biochar for agricultural purposes is much safer than the use of raw sewage sludge.

Abstract Biomass gasification produces energy from waste, but tar production limits the use of the produced syngas. Water scrubbing is commonly used to remove tar from gas. Based on absorption and impaction principles, a new water scrubbing unit was developed and tested using a statistical approach. The study focused on two key parameters: water flow rate and sampling time, which affect tar yield. Central Composite Design was used to optimize and understand how these parameters influence the results. The analysis showed that increasing the water flow rate and reducing the sampling time led to lower tar content. Optimal results were achieved with a water flow rate of 80 l/min and a sampling time of 10 minutes, producing minimal tar compared to other experimental setups. The developed tar scrubbing unit reduced tar content by up to 67%. Statistical analysis (ANOVA) revealed that the water flow rate significantly influenced tar reduction in syngas across all trials examined in this study. This reduction is crucial for enhancing the fuel value of syngas, underscoring its potential for diverse applications. In conclusion, this tar reduction unit effectively reduces tar in syngas from small and medium-sized gasifier plants, which helps improve fuel quality.

This study examines methane (CH4) emission factors from biogas and wastewater treatment plants, based on primary and secondary data collected from 109 facilities. Primary emission data were measured at 19 facilities representing prevalent plant configurations across Europe. Statistical analysis highlights two categorical variables, namely primary feedstock and plant size, expressed as CH4 production (≤250 kgh−1: small and medium-sized plants, >250 kgh−1: large plants), each of which has a significant impact on whole-site CH4 emissions. Additionally, digestate storage (gastight vs. not-gastight) has a meaningful effect when considering CH4 production as a continuous variable in the statistical analysis.Our results indicate that wastewater treatment plants have the highest average CH4 losses (7.0 % of CH4 produced, n = 31 or 0.10 kgpopulation equivalent(PE)-1yr−1, n = 28), followed by manure-based plants (3.7 %, n = 49), biowaste treatment facilities (2.8 %, n = 11) and energy crop-processing plants (1.9 %, n = 14). Furthermore, small and medium-sized plants have elevated emissions (5.6 %, n = 67) compared to larger counterparts (2.2 %, n = 42), primarily attributed to the absence of gastight digestate storage. Emissions tend to be lower with gastight digestate storage (2.7 %, n = 61) than not-gastight storage options (6.2 %, n = 48).Emission factors were determined for normal operating conditions, with a further investigation into other-than-normal operating conditions revealing temporal or constant emission peaks in eight out of 19 facilities. These peaks, suggesting potential areas for targeted mitigation strategies, were attributed to pressure relief valves, flare ignition problems and major leakages.

Minimising greenhouse gas emissions from small and medium-sized wastewater treatment plants

This paper presents a model-based predictive control for an intermittently aerated bioreactor of a medium-sized wastewater treatment plant. The main objective of the proposed method is to develop an intermittent aeration sequencing control strategy to minimize the aeration system energy consumption, with a subscription to the EU effluent standards and the plant operating constraints. A multilayer control system with two levels is implemented. The optimization level uses a model predictive control algorithm to determine the optimal value for the aeration fraction of the aeration cycle. The lower layer provides a feedback control loop of the bioreactor dissolved oxygen and secures intermittent aeration sequencing. The obtained aeration sequence guarantees that the effluent fulfills the requirements following regulatory standards for wastewater discharged. The control system demonstrates good performances for both setpoint tracking and disturbance rejection. Important energy savings are also obtained when comparing the developed control strategy to traditional control systems based on a pre-determined aeration sequence.

The role of small and medium enterprises in the economic development of nations cannot be overstated. These businesses, ranging from small family-owned bakeries to medium-sized manufacturing plants, play a vital role in job creation, innovation, and overall economic growth. Numerous studies have established the crucial significance of SMEs to economic success and the development of regions. Our research aims to investigate the extent to which SMEs in Algeria contribute to the country’s economic development and diversification. Considering the economic status of Algeria as a developing nation heavily reliant on oil revenues, it presents a unique case for study. To achieve our research objectives, over 120 official government reports published between 2001 and 2022 are analysed. Descriptive data analysis was conducted, and the Entropy index was calculated to address the problematics and verify the hypotheses. The results reveal that SMEs in Algeria make considerable contributions to employment rates and GDP values. However, their numbers in export operations are very low. The study found that SMEs in Algeria are potent locally, but their performance in global markets is very poor.

Hydropower plants with a small installed capacity, which are widely distributed in mountainous areas with abundant rainfall and steep rivers, play an important role in resolving energy problems in remote rural areas. These plants are a crucial source of clean electricity generated from water power. Harnessing local water resources not only helps alleviate energy shortages, but also reduces reliance on fossil fuels, contributing significantly to China’s national goals of achieving peak carbon emissions and carbon neutrality. This study investigates the carbon footprint of the Huangshadong Reservoir Project in Chongqing, China. The entire life cycle of the hydropower plant is assessed, including the preparation, construction, operation and maintenance, and demolition phases. The uncertainty was evaluated using the error propagation method. Following analysis, suggestions for carbon footprint reduction measures were proposed. Results showed that the total carbon footprint and the carbon intensity of the Huangshadong Reservoir Project over its entire life cycle are 33,148.29 t CO2e and 417.75 g CO2e/kWh, respectively. Of the total carbon footprint, the preparation phase, construction phase, operation and maintenance phase, and demolition phase account for 0.04%, 67.06%, 26.2%, and 6.7%, respectively. It means that the requirement for cement during the construction phase represents an important contribution to the entire life cycle carbon footprint of a small hydropower plant. As an integrated water conservancy project, the carbon intensity of the Huangshadong Reservoir Project is higher than that of medium-sized and large hydropower plants. However, its carbon intensity is lower than the emission factor of fossil power plants. The research results provide reference for both planning and construction of small hydropower plants and low-carbon development of rural hydraulic engineering.

One of the challenges in energy supply for isolated power systems is maintaining a steady balance between generated and consumed energy. The application of energy storage systems and flexible energy sources is the most preferable approach for these systems. Small- and medium-sized nuclear power plants are promising, carbon-free options for energy supply to isolated power systems. However, these plants have low maneuverability. To solve this problem, this article discusses the use of a thermal accumulator using a phase change material (solar salt) to heat feedwater. Tubes with longitudinal fins are used to intensify heat transfer in the storage system. This paper presents a method for calculating heat transfer along the entire heat exchange surface of such an accumulator. A series of 2D simulations were conducted to study the solidification process of solar salt around a heat exchange tube at various temperatures on the inner wall surface. The regression dependences of heat transfer on the temperature of the inner surface of the wall and the thickness of the solid PCM layer were determined. Using the presented method and the obtained regression dependencies, we determined the time graphs of the temperature change in the heat transfer fluid at the outlet of the accumulator during discharge. Based on the results presented, it was found that an accumulator with 72.7 tons of solar salt (dimensions: 6 × 3.71 × 2.15 m) can replace a high-pressure heater №1 at a low-power nuclear power plant (50 MW) during 3450 s.

Sludge drying is a key step in municipal sludge treatment. After mechanical dewatering, the water content of sludge is usually between 50% and 70%, which needs further drying. The main drying technologies include thermal drying, solar drying, ultrasonic drying and microwave drying, among which thermal drying technology is the most mature. Research shows that low-temperature drying technology has obvious advantages in reducing the release of harmful substances, energy consumption and cost. In terms of technology application, domestic sludge drying process is mainly divided into direct drying and indirect drying. Direct drying directly evaporates water through high-temperature gas, while indirect drying makes use of heat conduction effect to contact with high-temperature media. At present, indirect drying technology is mainly used in China, such as paddle type, disc type and thin layer drying. In particular, the low-temperature heat pump drying technology excels in terms of safety, footprint and energy consumption, with its ability to operate at lower temperatures, reduce the release of hazardous gases, and achieve environmental and economic benefits in a closed-cycle mode. This technology is suitable for small and medium-sized wastewater treatment plants and shows clear advantages in cases of budgetary constraints.

The dairy sector is recognized as a crucial element of India’s agriculture, contributing significantly to rural livelihoods and the national economy. This study aimed to investigate the efficiency and cost structures of various milk marketing channels in Karnataka. Data were collected from vendors, farmers, and administrative officials, as well as secondary data from commercial dairy plants, to analyze the input-output relationships and marketing efficiency across different channels. Two major districts, Mandya and Dharwad, were selected, and ten creameries, ten milk vendors, four medium-sized dairy plants, and one large commercial dairy plant were examined. Milk marketing channels were categorized into organized and unorganized systems, and the costs and returns associated with each type of intermediary were assessed. The analysis revealed considerable variations in marketing costs and efficiency. Channels with fewer intermediaries, such as direct sales from producers to consumers (Channel-I), were found to have higher efficiency. Conversely, channels involving multiple intermediaries, like those including creameries and vendors (Channel-IV), exhibited higher price spreads and lower efficiency. For instance, Channel-V demonstrated the highest marketing efficiency of 3.94, while Channel-IV showed the lowest efficiency at 2.03. It was observed that a higher number of intermediaries correlated with a larger price spread and reduced marketing efficiency. The study highlighted the need for improving marketing channels and strengthening linkages between farmers and organized sectors to enhance overall productivity and profitability in the dairy industry.