Optimal Environmental Conditions Research Articles

Developing a digital management system for museum collections using RFID and enhanced GIS technology

In recent years, the integration of Radio Frequency Identification (RFID) technology with deep learning has revolutionized the Internet of Things (IoT), leading to significant advancements in object identification, management, and control. Museums, which rely heavily on the meticulous management of collections, require precise and efficient systems to monitor and oversee their valuable assets. Traditional methods for tracking and managing museum collections often fall short in providing real-time updates and ensuring optimal environmental conditions for preservation. These shortcomings place a considerable burden on museum staff, who must manually track, inspect, and maintain extensive collections. This study addresses these challenges by proposing an advanced electronic management system that leverages the synergy between RFID technology and Geographical Information Systems (GIS). By integrating an enhanced LANDMARC algorithm into our geoinformation framework, the system visually represents the real-time location of museum collections on custom electronic maps, significantly improving the accuracy and timeliness of environmental monitoring. Additionally, RFID technology is utilized to continuously identify the real-time location of museum staff, facilitating the evaluation of their inspection tasks. This dual approach not only enhances the operational efficiency of collection management but also supports the development of intelligent, automated systems for museums, advancing the application of RFID technology in item identification and location management.

Predicting the Global Potential Suitable Areas of Sweet Osmanthus (Osmanthus fragrans) Under Current and Future Climate Scenarios.

Osmanthus fragrans is a valuable landscaping tree that is appreciated worldwide. However, the optimal environmental conditions for O. fragrans cultivation have yet to be studied in detail, which hinders the preservation of wild resources of this plant and its commercial exploitation. The maximum entropy model was applied to assess the significance of environment variables influencing O. fragrans distribution. Combining data from 629 global distribution points for O. fragrans, predictions were made on the potential effects of climate change on the geographical distribution of suitable habitats for this species in the present and the future. The results indicated that O. fragrans preferred a warm and humid growing environment. Under the current climatic conditions, the potential habitats for O. fragrans were mostly located in the eastern coastal areas of the continents at medium and low latitudes. The main environmental variables that affected its distribution were the precipitation during the warmest quarter, the temperature seasonality, and the mean temperature of the warmest quarter. The analysis indicated that the continuation of current trends in climate change will result in the further reduction of suitable habitats for O. fragrans growth, and the global centroid will shift to the southeast. These findings provided insight into the impact of climate change on O. fragrans habitats, as well as provide guidance for the conservation of wild resources of this species and the breeding of more climate change-resistant varieties for the future.

Rancang Bangun Pakan Ikan Otomatis dan Kontroling Suhu Serta Monitoring pH Air Berbasis IoT

This research proposes the design of an automatic fish feeding system equipped withtemperature control and water pH monitoring based on the Internet of Things (IoT). Thissystem aims to increase efficiency in aquarium or fish pond management by integratingvarious control and monitoring functions in real-time. In this system, the automatic fishfeeder uses a programmable dispenser mechanism to provide feed in predeterminedamounts and times. Temperature control is carried out using temperature sensors andheating or cooling actuators, to maintain water temperature conditions within the optimalrange. In addition, water pH monitoring is carried out through a pH sensor connected tothe system to ensure the water quality remains ideal for fish health. Data from these sensorsis sent in real-time to the IoT platform, enabling remote monitoring and control via webbasedor mobile applications. The results of implementing this system show increasedefficiency in feeding, increasing operational efficiency, reducing human error, andproviding quality fish, as well as maintaining more stable and optimal environmentalconditions. The implementation of this system shows great potential in modern aquacultureapplications by utilizing IoT technology for better and responsive management.

Assessment of Abiotic Factors for Sea Turtle Nesting Suitability in Coastal Bays

Cilacap Bays, critical nesting areas for sea turtles, face growing habitat disturbances from tourism. However, studies on nesting suitability in these regions remain scarce. This research assesses the abiotic factors influencing sea turtle nesting in Cilacap Regency, Indonesia, across eight observation stations. Key ecological parameters—land surface temperature (28°C - 36.3°C), pH (mean 6.8), sand particle size (0.212-0.500 mm), beach slope (11.50%-20.99%), and beach width (28.8m-81.8m)—were evaluated. The results highlight Sidaurip Beach as the most suitable for nesting due to optimal environmental conditions, with Station (SP1) being particularly favorable for producing male hatchlings due to its suitable 28°C temperature. These findings suggest targeted egg relocation to SP1 could help address gender imbalances, ensuring long-term population sustainability. This research provides valuable insights for sea turtle conservation and supports future policy efforts to protect nesting sites in Cilacap amidst growing environmental pressures

Fe and Mn Removal from Acid Mine Drainage by Utilizing Chlorella sorokiniana and Monoraphidium neglectum as Biosorbent

The mining industry generates acid mine drainage (AMD) characterized with a low pH value and high dissolved metal concentration that leads to the negative impacts on the environment and human health. The objectives of this research were to investigate the growth response of mixed culture of microalgae Chlorella sorokiniana and Monoraphidium neglectum in a liquid media contaminated with AMD; generate the optimum environmental conditions (pH value and contact time) to determine the efficiency biosorption of iron and manganese contained in the solution of AMD into the consortium of microalgae; and quantify the maximum removal amount of iron and manganese contained in the solution of AMD by utilizing microalgae consortium of Chlorella sorokiniana and Monoraphidium neglectum as biosorbent. AMD used in this research was characterized with a pH value of 1.65 with iron and manganese concentrations of 8.28 mg/L and 4.57 mg/L. The research of biosorption was conducted in 150 rpm with pH level variations of 4, 5, and 6, and contact time variations of 60, 120, and 180 min. The maximum value of iron and manganese removals occurred when pH level reached 5 at 180 min of contact time with removal efficiency of 89.73% for iron and 94.53% for manganese. The results proved that the mixed culture of microalgae namely Chlorella sorokiniana and Monoraphidium neglectum can be utilized to remove iron and manganese contained in acid mine drainage.

Influence of Environmental Conditions on Bacterial Remediation of Oil-Contaminated Soil: A Case Study at Baiji Refinery

Total Petroleum Hydrocarbons (TPH) are a major environmental pollutant, posing serious risks to soil health and ecosystems. TPH contamination, often resulting from crude oil spills and industrial activities, significantly disrupts soil structure, reduces fertility, and hinders the growth of plants and soil-dwelling organisms. In the environment, TPH compounds persist due to their hydrophobic nature, leading to long-term ecological damage. They can infiltrate groundwater, compromising its purity and presenting health hazards to humans and wildlife. The existence of TPH in soil modifies the population of bacteria, reduces biodiversity, and impedes natural processes such as nutrient cycling. Effective bioremediation techniques, such as microbial degradation, are essential for mitigating the harmful impacts of TPH on soil and the broader environment. This study emphasizes the urgent need for sustainable remediation strategies to restore contaminated soils and protect ecological and human health. This study investigates the influence of environmental circumstances on bacteria employed for the remediation of soil polluted with crude oil, focusing on bacterial strains sourced from the Baiji refinery in Iraq. Microbial rehabilitation is an economical and environmentally sustainable method for decomposing hydrocarbons into simpler molecules, making it an effective method for soil bioremediation. The study monitored biodegradation over seven months, assessing the degradation efficiency of total petroleum hydrocarbons (TPH) using gas chromatography-mass spectrometry (GC-MS). Environmental factors, including temperature, moisture levels, and nutrient availability, were closely monitored to assess their impact on bacterial activity. Ideal moisture range for bacterial growth and hydrocarbon degradation is often cited as 40% to 60% of the soil's WHC. Too much water can reduce oxygen availability in the soil, inhibiting aerobic bacterial growth, while too little water can limit microbial metabolism. Temperature affects bacterial metabolism and the rate of hydrocarbon degradation. Most hydrocarbon-degrading bacteria thrive in mesophilic conditions. The ideal temperature range for TPH degradation by bacteria is generally between 25°C and 35°C. At temperatures below 15°C, microbial activity and degradation rates slow significantly, while temperatures above 40°C can inhibit bacterial growth or even kill the microbes. The results revealed that the moisture: 40%–60% of soil's water-holding capacity and temperature 25°C–35°C maintaining these conditions promotes the optimal breakdown of hydrocarbons in bioremediation efforts. The results revealed significant degradation of crude oil, with a reduction of 40 initial compounds in untreated samples to 25-35 compounds in treated samples. The biodegradation rates increased steadily over time, with a removal efficiency reaching 72.38% by the end of the experiment. Additionally, the study demonstrated that environmental conditions, particularly temperature and moisture, play a pivotal role in optimizing bacterial degradation activity. These findings underscore the potential of bacteria in bioremediation efforts and the necessity of optimal environmental conditions, such as controlled temperature, moisture content, and nutrient levels, are essential for maximizing the efficiency of crude oil degradation in contaminated soils.

Estimating Energy Needs for Climate-Controlled Greenhouses in Syria with a Software Tool

Amid the current conditions in Syria, the study of energy consumption within plastic greenhouses emerges as a fundamental element in the agricultural economy, especially in areas subject to extreme climate variations. With many thermal power stations ceasing operation due to conflicts and the diminishing sources of energy, understanding energy consumption becomes more urgent to enhance productivity and reduce costs. Successful management of protected agriculture requires in-depth knowledge of weather dynamics and the optimal environmental conditions for crops. To implement effective management of plastic greenhouses, it is essential to recognize how climatic fluctuations affect plant growth and production throughout the various seasons. Heating systems form a significant part of the costs in constructing plastic greenhouses, and deficiencies in these systems can lead to negative impacts on quality, quantity, duration of cultivation, and production volume. Therefore, accurately calculating heating costs is crucial for reducing operational expenses. This study included the development of a computer program to determine the heating needs of plastic greenhouses, considering various factors such as the geographical location of the greenhouse, crop type, covering materials, heating system used, and land area. The results showed that Syria needs 4.56 megawatts of energy for the greenhouses, with the Tartus Governorate consuming the largest share, with energy consumption rates in Tartus, Latakia, Homs, and Damascus countryside amounting to 3.6, 0.3, 0.51, and 0.19 megawatts, respectively. The crops of tomatoes, vegetables, strawberries, and tropical plants consumed 2.2, 1.66, 2.21, and 0.244 megawatts of energy, respectively. This study is an important step towards achieving sustainable and efficient agriculture that contributes to supporting the economy and protecting the environment in Syria.

Quality and Processability of Meat in Polish Native Pigs – A Review

Abstract The primary aim of pig breeding efforts is to produce animals characterized by outstanding performance, including also fattening and slaughter performance traits. However, improved carcass leanness and reduced carcass fatness, especially intramuscular fat content, have led to a deterioration of pork quality and processability. Due to the growing frequency of meat defects and the limited potential use of such meat in the production of premium products this constitutes a considerable problem for the meat industry. The breeds superior in terms of meat quality are native pig breeds, such as those kept in Poland, i.e. Pulawska (Pul), Zlotnicka Spotted (ZS) and Zlotnicka White (ZW) pigs. The aim of this paper is to present a review of research results concerning quality and processability of meat produced by the Polish native pig breeds. The presented results indicate that pigs of local breeds exhibit a low level of performance traits (daily gain, carcass leanness, backfat thickness) while maintaining very good parameters of meat quality and processability (muscle composition and physical properties, fatty acids profile, sensory traits). Thus, they are used as a source material for premium products. In view of the small size of local populations and higher production costs in Poland it is a niche production. Therefore, the current aim of breeding indigenous breeds is both to maintain a safe population size and genetic diversity and to increase popularity of their meat and processed meat products among consumers. This objective is attained, among other things, thanks to efforts to reduce cost of their production through optimization of environmental conditions and wider use of less expensive traditional feed formulations, which make it possible to fully utilize the potential of local pork resources.

Envisioning a decision support system for the planning of alternative fuel bunkering operations in Singapore

Abstract In the coming decades, the global maritime industry will face a most formidable technological and societal challenge set by climate change – achieving net zero carbon emissions by 2050. To meet this target, ships are shifting towards the use of low-carbon alternative fuels such as ammonia and methanol. While this paradigm shift to the bunkering of greener fuels is encouraging, it also introduces a new and unique type of environmental risk in the unfortunate scenario of a spill. In the past decades numerous environmental studies have been conducted and mitigation techniques for petroleum oil spills have been developed. However, ammonia and methanol spills are comparatively less understood globally and in the region. There is a significant knowledge gap regarding how the complex atmosphere, hydrodynamic and environmental conditions of the Singapore Straits may influence the dispersion and assimilation of hypothetical ammonia or methanol plumes. Together with other emerging alternative fuels such as electricity and hydrogen, ammonia and methanol have different physical and chemical properties in ambient water compared to conventional LNG or petroleum oil which makes modelling the risk they pose to the environment more challenging. In view of these challenges, the key objective of our research is to develop an operationally running decision support system (DSS) that combines physics-based atmospheric and coastal hydrodynamic models that can forecast the marine and atmospheric plume dispersion of alternative fuels. This forecasting capability will be supplemented with data-driven and rule-based optimisation algorithms that can be used to determine the optimal mitigation scenarios which minimises the potential environmental impacts. Overall, the DSS will integrate observation data, models, mitigation scenarios, and decision-making tools pertaining to efficient and safe bunkering operations within Singapore’s ports. This is essential as the use of alternative fuels in maritime industry becomes more common in Singapore and around the world. Such a system will aid relevant authorities to better calculate risk and plan mitigation measures at designated bunkering locations and periods having optimal atmospheric, hydraulics, and environmental conditions. In this paper, we describe the potential consequences of alternative fuel spills, mitigation measures and a plan for assessing their environmental impact within the context of Singapore. We will review the limited current efforts to model ammonia spills in the literature and propose for a more integrated modelling approach through the DSS.

Optimization of a Smart Greenhouse with a Solar Energy System for Floating Raft Hydroponic Cultivation: Implementation and Performance Evaluation

Abstract The rapid growth of the global population has increased food demand, posing challenges for traditional agriculture due to limited natural resources. Hydroponic systems offer a sustainable solution by optimizing the growing environment. This study evaluates the performance of a floating-raft hydroponic smart greenhouse powered by solar energy. The system integrates advanced technologies and renewable energy sources, including three 120 Wp and 130 Wp solar panels arranged in a series-parallel configuration, a solar charge controller, two parallel 12V 65Ah and 12V 200Ah batteries, a microcontroller, DHT22 sensors, and actuators such as LED lights and a mist-type DC pump sprayer. These components effectively regulate humidity, temperature, lighting, and spraying, with data transmission to the Antares platform via a monitoring system utilizing NodeMCU ESP8266. The greenhouse maintained optimal environmental conditions, reducing the temperature from 38°C to 32°C within 30 minutes. The system’s daily electrical load was 1006.36 Wh, leaving an energy reserve of 68.35%. The plants cultivated in the greenhouse responded favorably to the system. This study highlights the potential of combining renewable energy with smart agricultural technologies to address the limitations of traditional farming practices and enhance sustainability.

Impacts of Various Lighting Programs on Chicken Production and Behavior – A Review

Abstract Environmental changes have an impact on agriculture, especially the production of poultry. These changes have caused grave concerns that will negatively affect the health and productivity of chickens. We must consider illumination, density, and dietary aspects when determining the optimal environmental conditions for poultry rearing and output. Each of these variables influences the performance and behavior of birds uniquely. A crucial aspect of evaluating animal well-being is that it understands animal behavior. Artificial lighting has been widely investigated in poultry production over the last fifty years to enhance muscle gain and egg production while preserving an effective feed conversion ratio, bird health, and well-being. Yet, researchers and breeders still disagree over the ideal light quality and quantity, density, and feeding levels for poultry farming, particularly for chickens. This evaluation, therefore, covered the most up-to-date practical methods for enhancing illumination, density, and feeding-related aspects of poultry behavior, health, and production.

Effect of storage conditions on host egg suitability and the reproductive fitness of Oobius agrili (Hymenoptera: Encyrtidae), an egg parasitoid of the invasive emerald ash borer (Agrilus planipennis) (Coleoptera: Buprestidae).

Oobius agrili Zhang and Huang (Hymenoptera: Encyrtidae) is an important egg parasitoid of the emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae). Methods for laboratory-rearing O. agrili have been developed but its mass-production depends on the continuous production and storage of freshly laid EAB eggs as well as diapaused parasitoid progeny (inside parasitized EAB eggs). The purpose of this study was to determine optimal environmental conditions for long-term storage of host eggs as well as diapaused parasitoid progeny. Fresh host eggs and diapaused parasitoid progeny were stored at two low storage temperatures (1.7 and 12.8 °C) and three levels of relative humidity (low ~31%, medium ~74%, and high ~99.9%) for various length of time (15-270 days) and then evaluated for host egg suitability and the reproductive fitness of stored parasitoid progeny. EAB eggs were stored for approximately 30 days without significant reduction of their viability and suitability to O. agrili parasitism at low storage temperatures under high and medium relative humidity. Neither storage temperature or humidity had any significant effects on adult parasitoid emergence for storage durations of up to 270 days. When storage durations were over 120 days, however, both adult parasitoid longevity and fecundity declined approximately 20-30% across all temperature and humidity treatments. Relevance of findings to mass-production and storage of O. agrili for biocontrol is discussed.

Photoperiod and temperature as dominant environmental drivers triggering chemical compositions of garlic bulb during growth

Photoperiod and temperature are crucial for plant growth and development, but the accumulation patterns and regulatory mechanisms of garlic in response to these factors remain unclear. Compared to normal conditions (12/12 h light/dark; 22/15 °C day/night), increasing the photoperiod by 1 h each month with normal temperature (13/11, 14/10, 15/9, 16/8 h; light/dark; 22/15 °C day/night) or increasing photoperiod by 1 h with a 1.5 °C increase in temperature (13/11, 14/10, 15/9, 16/8 h light/dark; 23.5/16, 25/17, 26.5/18, 28/19 °C day/night) at monthly intervals substantially affects garlic growth in early G204, mid-G666, and late G390 harvest cultivars. For both increased photoperiod and temperature, the environment most favorable for bulb growth is characterized by the maximum accumulation of hormones (IAA, JA, and ZT) during bulb formation, while higher levels of ACC, phenolic acids, and organosulfur compounds are observed during the harvesting stage. Furthermore, the accumulation patterns of alliin and allicin in garlic bulbs for G204, G666, and G390 cultivars significantly increased, with fold changes of (2.0, 1.8, and 1.9) and (1.8, 1.7, and 1.5), respectively, in response to increased photoperiod and temperature conditions. Additionally, the accumulation pattern in G204, and G666 was similar but notably distinct from late harvest G390 during growth. In this study, metabolomics models were constructed to assess chemical composition variations and predict the differences among three garlic varieties during the growth stages. These models revealed functional component variations and provided reliable predictions, offering valuable insights for estimating garlic chemical compositions and identifying optimal environmental conditions for growth.

Environmental drivers of mesozooplankton dynamics in the Munroe Island, adjacent to Ashtamudi Estuary, India.

The response of mesozooplankton is critical in assessing the health of an estuarine ecosystem. Reports on the spatial and temporal dynamics of mesozooplankton community in estuarine and backwaters of the Southern parts of India are scanty. In this scenario, we appraised the community structure of mesozooplankton and their spatio-temporal dynamics based on various multivariate statistical assessments. A total of 31 taxa were identified and the abundance was principally dominated by Copepoda followed by Luciferidae during three sampling seasons. The most abundant species were: Paracalanus parvus parvus, Pseudodiaptomus aurivillii, Temora stylifera, and Pseudodiaptomus serricaudatus. Canonical correspondence analysis and Spearman's correlation coefficients underlined that salinity, turbidity, conductivity, temperature, dissolved oxygen, chlorophyll a (Chl-a), and nutrients were the principal environmental variables strongly linked with mesozooplankton dynamics in Munroe Island. The highest abundance of mesozooplankton was recorded in MoN (monsoon), followed by PrM (pre-monsoon), and PoM (post-monsoon). Hierarchical clustering confirmed that the grouping of sampling stations is based on the estuarine and freshwater influences on mesozooplankton abundance. During the entire investigation, various ecological indices were observed in good condition. Moreover, the optimum environmental conditions during the PoM season are marked with the highest indices values. Overall, multivariate investigations undoubtedly proved the suitability of mesozooplankton communities as potential bioindicators for spatial and seasonal ecological assessments. Our investigation emphasizes the high assemblages of mesozooplankton and their responses to various environmental variables and highlights the significance of long-term ecological monitoring in a threatened ecosystem like Munroe Island.

Can acclimation of freshwater rotifers to silver nanoparticles or 5-fluorouracil influence their multi- and transgenerational effects?

Emerging chemical contaminants (ECCs) are among the major environmental threats in present century. A variety of ECCs is released into aquatic environments with little knowledge about their long-term impacts to organisms. We examined the role of acclimation of the freshwater rotifer Brachionus calyciflorus to silver nanoparticles (Ag-NPs) and 5-fluorouracil (5-FU) for determining their ability to deal with these ECCs individually and in mixtures along multiple generations. Additionally, transgenerational effects were also assessed during the recovery phase. Rotifers acclimated at EC10 of Ag-NPs along generations showed a higher ability to deal with higher concentrations of these nanoparticles or 5-FU along generations. Rotifers acclimated to EC10 of 5-FU showed varied responses, as their population growth rates were affected at the initial generations once exposed to higher concentration (EC50) of the same or a new contaminant; however, the rotifers acquired resistance in later generations. The exposure of generational Ag-NP-acclimated rotifers to the mixture of Ag-NPs and 5-FU at EC50 led to a shift from no effects to negative effects along successive generations, suggesting a decrease in resistance, which remained even in the post-exposure recovery phase. Similar transgenerational adverse effects were also observed for the generational Ag-NP-acclimated rotifers released from 5-FU. Rotifers acclimated to 5-FU showed a decrease in population growth rate at the first generation of recovery phase, possibly shifting their optimal environmental conditions when released from contaminants. Overall, our results suggest that rotifers had a high level of plasticity to ECC exposure in freshwaters; however, acclimation can be generic or contaminant dependent.

Evaluation of bread wheat germplasm for adult plant resistance to stem rust using artificial inoculation

Wheat stem rust, caused by Puccinia graminis f.sp. tritici, is a major biotic threat to wheat (Triticum aestivum L.) in many wheat-producing countries worldwide, including Ethiopia. The pathogen is capable of continuously evolving new fungal races with high reproductive potential. It can be easily dispersed by wind over large geographic areas, allowing it to attack resistant varieties. Under optimal environmental conditions, it can cause epidemics leading to severe yield losses (up to 100%). A total of 91 germplasms, comprising 81 advanced bread wheat lines and 10 varieties, including the susceptible check Morocco, were planted using an augmented design. The experiment was conducted with artificial inoculation on spreaders to evaluate their slow rusting response against four virulent stem rust races viz. TTKTF, TKKTF, TTKTT, and TTTTF under field conditions at the Kulumsa Agricultural Research Center during the 2022-2023 offseason. Slow rusting resistance at the adult-plant stage was assessed by measuring the final rust severity (FRS) and the average coefficient of infection (ACI). Accordingly, 50 (61.7%) of the advanced lines and 6 (60%) of the released varieties namely Boru, Abay, Shaki, Kakaba, Deka, and Dursa exhibited low levels of FRS and ACI. In contrast, 31 (48.3%) of the advanced lines and 4 (40%) of the varieties showed high FRS and ACI values. The germplasms with low FRS and ACI values were considered to exhibit good slow rusting resistance and could be recommended for release into production and/or used in breeding programs aimed at achieving durable stem rust resistance in Ethiopia.

Farmed crickets (Orthoptera: Gryllidae) raised with dermestids (Coleoptera: Dermestidae) suffer from reduced and delayed growth, but not enough to explain reports of dramatic yield loss.

The mass production of insects for food and feed is an expanding North American industry. Facilities that mass rear insects are at risk of pest infestations because the optimal environmental conditions for rearing beneficial species may also support the development of pest species. Here, we present the first recorded results detailing the interactions between dermestids and farmed crickets. Cricket farms have reported extremely low harvest yield during heavy dermestid infestations, but the exact reasons for this low yield are unknown. Many dermestid larvae are covered in dense, detachable, barbed setae called hastisetae, which are used by the larvae as an active trapping system against arthropod predators. We designed a series of experiments to test the hypotheses that a dermestid pest of cricket farms, black larder beetle (Dermestes ater DeGeer (Coleoptera: Dermestidae)), may be directly impacting Gryllodes sigillatus Walker (Orthoptera: Gryllidae) yield through the physical effects of hastisetae ingestion and/or indirectly impacting cricket yield through competition for fishmeal, a primary source of protein in conventional cricket feed. Our predictions that G. sigillatus life history and survival would be negatively affected by dermestids were largely refuted. Females fed infested diets grew less mass, but not smaller body size, compared to females fed uninfested diets. We also found that while G. sigillatus experienced delayed growth early in life after living with dermestids, they were able to tolerate living with, and consuming, dermestid larvae. We discuss how these findings have led to new hypotheses concerning how dermestid infestations drive reductions in cricket farm yield.

Should a single growth standard be used to judge the nutritional status of children under age 5 years globally: Yes

Childhood nutritional status serves as a lens through which nations and communities identify missed opportunities to improve health and wellbeing across the life cycle, as well as economic development and other related sectors. Countries have committed to the global nutrition targets endorsed by the World Health Assembly in 2012, which were included in the Sustainable Development Goals framework under the target to end all forms of malnutrition by 2030. The child malnutrition indicators for tracking countries’ progress toward the agreed-upon targets are based on standard definitions of nutritional status against the widely adopted and used World Health Organization (WHO) Child Growth Standards. The standards were based on a sample of healthy breastfed infants and young children from diverse ethnic backgrounds and cultural settings as part of the WHO Multicentre Growth Reference Study. The WHO Child Growth Standards developed represent the best description of physiological growth for children aged <5 y. The standards depict normal early childhood growth under optimal environmental conditions and can be used to assess children everywhere, regardless of ethnicity, socioeconomic status, and type of feeding.

Enhancing arsenate removal through interpretable machine learning guiding the modular design of metal–organic frameworks

The modular design of metal–organic frameworks (MOFs) for enhancing arsenate (As(V)) adsorption remains a challenge. We have developed twelve interpretable machine learning prediction models by integrating six decision tree-based algorithms with two molecular fingerprints, Morgan and MACCS. The optimal XGBoost-Morgan model, with its high determination coefficient of 0.97 and low root mean square error of 11.78, not only demonstrates excellent prediction and generalization capabilities in As(V) adsorption capacity, but also validates the feasibility of modeling concepts by feature engineering adopted in this work. Our comprehensive model interpretation initiates with the molecular fragment composition of the organic linkers, the secondary building units, and the topological nets, that constitute MOFs, and structure parameters. It culminates in the proposal of a reticular chemistry design scheme specifically tailored for the adsorption of As(V) by MOFs. Furthermore, it delineates the optimal environmental conditions conducive to effective As(V) adsorption. We anticipate that our MOF design strategy will be extensively applicable to the target removal of pollutants.

Analysis of suitable regions for microalgae cultivation and harvesting potential for carbon capture: A global feasibility study

Microalgae, have the ability to capture CO2 and the potential for biofuel production. However, scaling up capturing carbon by microalgae is not feasible worldwide because of difference in weather conditions. Hence, identifying favorable regions for capturing carbon by microalgae is the initial step in commercializing this industry. In this research, a global feasibility study has been conducted to analyse the potential of microalgae cultivation and harvesting to capture CO2, based on carbon emissions, weather conditions, and the boundary of countries. A total of 454 cities were selected for this research, and the amount of microalgae productivity and carbon capture rate in each area was calculated according to the optimal environmental conditions for microalgae growth. Methodology and results have been illustrated using Geographical Information System (ArcGIS 10.8) to provide better visual insight for researchers. The results showed that the average microalgae productivity in Open Ponds (OP) and Tubular Photobioreactors (TPBR) is 132.63 T/ha/y and 78.26 kg/m3/y, respectively. Additionally, the average carbon capture rate by microalgae in OP and TPBR is 37.60 T/ha/y and 40.83 kg/m3/y, respectively. The study also revealed that microalgae will have a higher productivity in OP than in TPBR for 158 regions according to the first scenario, while the number of these areas will decrease to 58 and 29 under the second and third scenarios, respectively. Moreover, the global average potential energy content resulting from microalgae cultivation in OP is 4.854*106 MJ/ha/y. Therefore, selecting suitable regions regarding weather condition and type of cultivation system, is the most significant factors in outdoor commercial scaling up of carbon capture by microalgae.