High Energy Demand Research Articles

Energy Consumption Trends and Determinants in Polish Hospitals: Implications for Energy Efficiency Strategies

In the construction sector, hospitals are the buildings with the highest energy consumption. Due to the high demand for energy, hospitals’ energy efficiency is becoming very important. This study aims to examine the trends and factors that determine energy consumption in Polish hospitals from 2010 to 2019, highlighting the impact of hospital size and medical activities on energy efficiency. The analysis was carried out using data from 3061 hospital reports obtained from the e-Health Center, a state budgetary unit established by the Minister of Health. To measure and compare the efficiency of energy usage in hospitals, we developed eight energy usage efficiency indexes based on hospital size and medical activity. The size of the hospitals was described by the number of beds, operation rooms, doctors, nurses, and fixed assets value. Hospital activity was measured by the number of person-days, patients, and operations. Statistical analysis was carried out using StatSoft Statistica software version 13.3. The results show that larger hospitals are more energy efficient across various measures of energy use than smaller hospitals. The findings revealed also several important relationships between energy usage and factors connected with size and hospital activity, such as the number of beds, patients and person-days, medical staff, operations, and fixed asset values, underscoring the necessity for customizing energy efficiency strategies. This research contributes empirical insights that can guide policymakers and hospital administrators in their endeavors to improve energy efficiency and promote sustainability within healthcare facilities.

Classification of Faults in Power System Transmission Lines Using Deep Learning Methods with Real, Synthetic, and Public Datasets

Every part of society relies on energy systems due to the growing population and the constant demand for energy. Because of the high energy demands of transportation, industry, and daily life, energy systems are crucial to every part of society. Electrical transmission lines are a crucial component of the electrical power system. Therefore, in order to determine the power system’s protection plan and increase its reliability, it is critical to foresee and classify fault types. With this motivation, the main goal of this paper is to design a deep network model to classify faults in transmission lines based on real, generated, and publicly available datasets. A deep learning architecture that was based on a one-dimensional convolutional neural network (CNN) was utilized in this study. Accuracy, specificity, recall, precision, F1 score, ROC curves, and AUC were employed as performance criteria for the suggested model. Not only synthetic but also real data were used in this study. It has been seen that the created model can be used successfully for both real data and synthetic data. In order to measure the robustness of the network, it was tested with three different datasets consisting of real, generated, and publicly available datasets. In the paper, 1D CNN, one of the machine learning methods, was used on three different power systems, and it was observed that the machine learning method was successful in all three power systems.

Operational optimization of a rural multi-energy system supported by a joint biomass-solid-waste-energy conversion system and supply chain

Biomass, as one of the most accessible renewable resources, could reduce dependency on fossil fuels and mitigate associated environmental impacts. With economic development and improved living standards, biomass in rural areas is converted into various forms of energy to meet high energy demands. However, existing studies on rural multi-energy system operations assume energy production from biomass is a given input parameter and consider it to be a fixed constant or subject to upper and lower bounds, independent of the biomass supply chain. Indeed, biomass energy production is significantly influenced by the collection, transportation, storage, and other processes within the supply chain. This work proposes a mixed integer linear program (MILP) for the joint optimization of an integrated rural multi-biomass-solid waste energy conversion system with a source-grid-demand-based biomass-solid waste supply chain (IRMBS-BSC system). The IRMBS-BSC system encompasses three sub-systems: the biomass-solid waste source sub-system, the biomass-solid waste grid sub-system, and the biomass-solid waste demand sub-system. Various biomass-solid wastes are classified, and a source model is established to evaluate their availability. Subsequently, a supply chain model is developed within the biomass-solid waste grid sub-system. Based on the available and transported quantity from the biomass-solid waste source sub-system and grid sub-system, a multi-energy system operation model, considering refined biomass conversion processes, is proposed. A case study involving a multi-energy system that integrates multiple rural community biomass-solid waste supplies is conducted. The results demonstrate that the proposed MILP, which considers the biomass-solid waste supply chain, can reduce energy imports during the load peak periods and can also decrease the overall operational costs of the multi-energy system.

Metatranscriptomic insights into the dengue patient blood microbiome: Enhanced microbial diversity and metabolic activity in severe patients.

Dengue is the most re-emergent infection, with approximately 100 million new cases reported annually, yet no effective treatment or vaccine exists. Here, we aim to define the microbial community structure and their functional profiles in the dengue positive patients with varying disease severity. Hospital admitted 112 dengue-positive patients blood samples were analyzed by dual RNA-sequencing to simultaneously identify the transcriptionally active microbes (TAMs), their expressed genes and associated pathways. Results highlight that patients with severe dengue exhibited increased microbial diversity and presence of opportunistic species (unique and core) which includes Bacillus cereus, Burkholderia pseudomallei, Streptococcus suis, and Serratia marcescens. The functional profile analysis revealed enriched metabolic pathways such as protein degradation, nucleotide biosynthesis, ion transport, cell shape integrity, and ATP formation in severe cases, indicating the high energy demands and adaptability of these microbes. Our metatranscriptomic approach provides a species-level characterization of blood microbiome composition and reveals a heightened diversity of TAMs in patients with severe dengue, underscoring the need for further research into the role of blood microbiota in disease progression. Comparing the microbial signatures across the severity classes early in the disease offers unique potential for convenient and early diagnosis of dengue infection.

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars.

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans' robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%-65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.IMPORTANCEThe robustness of B. coagulans makes it a valuable microorganism for biotechnology applications; yet, this phenotype is not well understood at the cellular level. Through phenotypic characterization and systems analysis, this study elucidates the functional genomics and robustness of a novel, undomesticated strain, B. coagulans B-768, capable of utilizing inhibitory switchgrass biomass hydrolysates. The genome of B-768, enriched with carbohydrate metabolism genes, demonstrates high regulatory capacity. The coordination of proteome reallocation in Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) is critical for effective cell growth, sugar utilization, and lactate production via overflow metabolism. Overall, B-768 is a novel, robust, and promising B. coagulans strain that can be harnessed as a microbial biomanufacturing platform to produce chemicals and fuels from biomass hydrolysates.

BIM-based parametric energy analysis of green building components for the roofs and facades

Buildings are distinguished by their high energy demand over their lifespan. Iimproving energy efficiency in buildings necessitates mitigating the operation energy performance by evaluating more sustainable building components such as green infrastructures. The novelty herein is to conduct a BIM-based parametric energy analysis of green building components for the roofs and facades, taking into consideration the climate classification and orientation of the building. The proposed framework of this study uses Autodesk Revit software and Autodesk Green Building Studio as BIM tools, and Minitab software as a parametric analysis tool to estimate the energy performance of several alternative components based on Energy Use Intensity (EUI) and Annual Peak Demand (APD). A case study of a residential building is examined in four cities within different climate zones in Brazil; Rio de Janeiro (climate zone 08), Macaé (climate zone 05), Petrópolis (climate zone 03), and Nova Friburgo (climate zone 02). The base model design of components of the building includes a reinforced concrete roof and ceramic masonry façade. The utilized alternatives are roof components (i.e. green roofs and expanded clay roofs), and green façade. This work insight using green façade for all elevations and green roofs to enhance energy efficiency in terms of EUI by (10,17 %) in Rio de Janeiro, (6,67 %) in Macaé, (11,43 %) in Pertópolis, and (16,43 %) in Nova Friburgo. While the efficiency in terms of APD would be about (28,07 %) in Rio de Janeiro, (22,79 %) in Macaé, (21,67 %) in Pertópolis, and (12,58 %) in Nova Friburgo. When the construction project is designed to install a green façade to the main elevation only, this work recommends using green roofs rather than the expanded clay roof or the base model design roofs to increase energy efficiency in such types of buildings. This work contributes to integrating green building components into building designs to improve energy efficiency and empower decision-making and sustainability in buildings.

Achieving deep transport energy demand reductions in the United Kingdom

The transport sector is a crucial yet challenging area to decarbonize, given its heavy reliance on fossil fuel usage, carbon-intensive infrastructure and car-centric lifestyles. It remains the largest contributor to local air pollution in cities yet has the potential to improve people's physical and mental health. This research investigated the potential contribution of transport energy demand reduction to climate change mitigation and improving public health. Using a comprehensive bottom-up modelling framework, the Transport Energy and Air pollution Model (TEAM), this study provides an integrated assessment of the impacts of deep mobility-related energy demand reductions, including lifecycle carbon emissions, local air pollution and health impacts. Using a sociotechnical scenario approach and the UK as a case study, this research reveals that energy demand reductions of up to 61 % by 2050 compared to baseline levels are achievable and can enhance citizens' quality of life. Business as usual approaches which rely on a technical transition miss the legislated carbon budgets and result in higher energy demand in 2050. More comprehensive scenarios deliver a reduction of up to 72 % in total lifecycle carbon emissions by 2050, with approximately half of the reduction achieved through mode shifting and avoiding travel, while the other half comes from vehicle energy efficiency, electrification, and downsizing of the vehicle fleets. The research shows that it can lead to significant co-benefits such as improved local air pollution and public health. The feasibility and practicality of policy measures and integrated strategies identified for achieving deep transport-energy demand reductions are discussed.

7238 A rare cause of primary ovarian failure in an adolescent due to a genetic mutation in mitochondrial poly-A-polymerase (mTPAP) mRNA

Abstract Disclosure: J. Epstein: None. S. Veera: None. J. Pappas: None. B.C. Shah: None. Primary ovarian insufficiency (POI) is a dysfunction or loss of ovarian follicles with associated amenorrhea. While most causes are idiopathic, approximately 15% of POI cases are due to single gene or chromosomal abnormalities, such as X chromosome abnormalities. Many of these nuclear genes encode for proteins that function within the mitochondria. Mitochondrial disorders affect tissues with high energy demand, such as the neurological, skeletal, cardiac, and endocrine systems. Furthermore, mature ovaries have a relatively higher concentration of mitochondria, which play a role in cellular respiration along with steroidogenesis. Mutations that disrupt these pathways can therefore lead to ovarian dysfunction. We present a case of a 17-year-old female with concern for primary amenorrhea. She underwent pubarche at age 12 years and thelarche at 14 years, with slowed progression. Height Z score was -1.61 and weight Z score was -0.41. Lab work at presentation was significant for LH 18.6 IU/L (N 2.4-12.6 IU/L), FSH 43.9 IU/L (N 1.1-9.6 IU/L), low estradiol <2.5 pg/mL (N 30-100 pg/mL), low total testosterone 8.3 ng/dL (N 15-31 ng/dL), unremarkable HbA1C, cortisol, thyroid levels, and a 46 XX karyotype. Pelvic ultrasound showed small ovarian volumes with a 1.9 cc right ovary, 1.5 cc left ovary consistent with lack of hormonal stimulation, and uterus length of 4.9 cm (N > 4 cm) consistent with early hormonal stimulation. She was started on transdermal estrogen replacement. Past medical history included stable pericardial effusion, episodes of supraventricular tachycardia, pre-cataracts, speech delays, mild learning disabilities, spastic diplegia, progressive gait abnormalities, ligamentous laxity, and recurrent patellar dislocations requiring multiple orthopedic limb surgeries. Family history was significant for parental consanguinity as first cousins. As the etiology of the POI remained unknown, genetic testing was completed. Whole exome sequencing (WES) revealed a homozygous pathogenic variant in the MTPAP gene: p.(Leu495Arg) (CTG>CGG): c.1484 T>G in exon 9 on chromosome 10p11.23. MTPAP, also known as SPAX4, TENT6, or PAPD1, is a nuclear-encoded polymerase involved in synthesizing the 3’ poly(A) tail of mitochondrial transcripts as well as in mRNA degradation. She was diagnosed with autosomal recessive MTPAP-related neurodevelopmental and movement disorder. Monogenic disorders affecting mitochondrial function are rare causes of POI. A high index of suspicion should be raised when a constellation of neurological, musculoskeletal, and cardiac problems co-exist. WES can be a very useful tool for uncovering rare genetic disorders. Further studies are needed to clarify details of organ specific mitochondrial dysfunction and possible therapeutics in individuals affected with MTPAP-related neurodevelopmental and movement disorders. Presentation: 6/1/2024

7498 Pituitary Apoplexy Associated With COVID 19 Infection in a 55 Year Old Filipino Male: A Case Report

Abstract Disclosure: C.L. Macrohon: None. J.Y. Mercado: None. R.G. Gan: None. Introduction: Pituitary apoplexy is a rare fatal disorder resulting from acute ischemia or hemorrhage of the pituitary gland. Major predisposing factors include patients with anti-thrombotic drugs. However, there has been an increasing number of cases reported associating COVID- 19 and pituitary apoplexy. Case: This is a case of a 55-year-old Filipino male, who came in with right eye ptosis and blurring of vision associated with headache and dizziness. Significantly, 2 weeks prior the patient had developed cough and colds. On admission, he was noted to be febrile and presented with a visual acuity of light perception on the right eye and hand movements on the left. Plain MRI of the brain revealed a well-circumscribed hemorrhagic sellar-suprasellar mass with mass effect on adjacent structures worrisome for pituitary apoplexy. Incidentally, patient tested positive for COVID- 19. Hormonal work- up revealed hypopituitarism presenting with central hypothyroidism and hypogonadism. Patient was then started on Hydrocortisone 100mg intravenously as loading dose then 50mg intravenously every 6 hours to cover for adrenal insufficiency. At this point, thyroid hormone replacement was also started at 100mcg/day. Initially, patient was scheduled for endoscopic endonasal transsphenoidal surgery. However, due to euvolemic hyponatremia with a serum sodium of 119mmol/L secondary to SIADH, surgery was delayed and was performed on the fourth day of admission. Post- operatively, patient had improvement of vision and was eventually discharged stable without any complications. He was sent home on thyroid hormone replacement and steroids were discontinued since adrenal insufficiency was ruled out with a post operative serum Cortisol of 27.27ug/dL taken 24 hours after last dose of hydrocortisone. Discussion: COVID- 19 with associated hypophysitis or pituitary apoplexy has been reported in literature. The pituitary gland was proposed as possible targets of SAR- CoV-2 due to the presence of ACE- 2 receptors on the surface of their cells. Hazzi et al. discussed that infection by COVID-19 could play a role in the disruption of the equilibrium between the high energy demand and limited blood supply of underlying adenomas. They also discussed on possible routes of entry of COVID 19 particularly thru the nasopharyngeal epithelium via olfactory nerve or pass through blood brain barrier or thru the median eminence. Other possible contributing factors may be due to coagulopathy, endothelial dysfunction and hypercoagulative state seen in COVID- 19. Conclusion: With increasing reports of pituitary apoplexy in the setting of SARS-COV-2 infection there is a possibility that COVID 19 may be a risk factor for pituitary apoplexy. Hence, the prevalence of COVID- 19 may increase risk of patients with underlying pituitary tumors to develop pituitary apoplexy. Presentation: 6/2/2024

Stocking density affects growth, feed utilisation, metabolism, welfare and associated mRNA transcripts in liver and muscle of rainbow trout more pronouncedly than dietary fish meal inclusion level

In aquaculture, stocking density and diet composition are critical factors that influence the performance and welfare of the farmed animal. However, there is limited information on their interactive effects. In this context, applying a 2 × 2 factorial design, we conducted a 12-week feeding trial to evaluate the effect of stocking density (low, LSD: 3.3–15 kg m−3 and high, HSD: 5.8–25 kg m−3; initial-final values) and dietary fish meal content (high, HFM: 30 % and low, LFM: 15 %) on growth, feed utilisation, metabolic oxygen consumption, tissue indices, carcass composition, plasma metabolites, and transcriptional regulation of growth, metabolism and welfare-related biomarker mRNAs in liver and muscle of the juvenile rainbow trout. At the whole-animal level, the HSD group showed significantly higher routine metabolic rate and feed intake indicating higher energy demand; but growth and feed efficiency was lower in HSD than the LSD group. Morpho-anatomically, HSD fish had lower relative gut length and higher intra-peritoneal fat index than LSD fish. Lower plasma free amino acids and glucose levels reiterated high energy expenditure in HSD, and elevated albumin levels indicated potential oxidative stress in the HSD group. Correspondingly, at the transcriptional level, hepatic mRNA levels of antioxidative enzymes (sod, cat, gst, g6pd) and stress-related molecular chaperone hsp90 were up-regulated in HSD; while the transcript abundance of growth-axis markers (ghr, igf1 igf2) and nutrient-sensor mtor were decreased. In muscle, proteolytic pathway components fbx32 and murf1 were upregulated in HSD, and concurrently mtor was also upregulated suggesting higher protein turnover in this group. With respect to the effect of dietary fish meal inclusion levels, LFM showed decrease in growth, hepatic igf2 expression, and lower plasma triglycerides and free amino acid levels than HFM group. However, the sensory appearance of flesh was found to be slightly better in LFM. Significant diet-husbandry interactions were not observed phenotypically, but the mRNA abundance of hepatic markers (ampk1, hsp70, mhc1 and tnfa) linked to energy-sensing, stress and immune response were differentially regulated. Overall, the study shows that high stocking density has a greater degree of impact on fish growth and welfare than reduction in dietary fishmeal inclusion, with limited interactional effects.

Investigating the Future of Freight Transport Low Carbon Technologies Market Acceptance across Different Regions

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035.

Optimal dimensioning of renewable energy generation and storage systems

With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.

Effect of HPV Oncoprotein on Carbohydrate and Lipid Metabolism in Tumor Cells.

High-risk HPV infection accounts for 99.7% of cervical cancer, over 90% of anal cancer, 50% of head and neck cancers, 40% of vulvar cancer, and some cases of vaginal and penile cancer, contributing to approximately 5% of cancers worldwide. The development of cancer is a complex, multi-step process characterized by dysregulation of signaling pathways and alterations in metabolic pathways. Extensive research has demonstrated that metabolic reprogramming plays a key role in the progression of various cancers, such as cervical, head and neck, bladder, and prostate cancers, providing the material and energy foundation for rapid proliferation and migration of cancer cells. Metabolic reprogramming of tumor cells allows for the rapid generation of ATP, aiding in meeting the high energy demands of HPV-related cancer cell proliferation. The interaction between Human Papillomavirus (HPV) and its associated cancers has become a recent focus of investigation. The impact of HPV on cellular metabolism has emerged as an emerging research topic. A significant body of research has shown that HPV influences relevant metabolic signaling pathways, leading to cellular metabolic alterations. Exploring the underlying mechanisms may facilitate the discovery of biomarkers for diagnosis and treatment of HPV-associated diseases. In this review, we introduced the molecular structure of HPV and its replication process, discussed the diseases associated with HPV infection, described the energy metabolism of normal cells, highlighted the metabolic features of tumor cells, and provided an overview of recent advances in potential therapeutic targets that act on cellular metabolism. We discussed the potential mechanisms underlying these changes. This article aims to elucidate the role of Human Papillomavirus (HPV) in reshaping cellular metabolism and the application of metabolic changes in the research of related diseases. Targeting cancer metabolism may serve as an effective strategy to support traditional cancer treatments, as metabolic reprogramming is crucial for malignant transformation in cancer.

Novel energy efficient integration of chimney ventilation, liquid desiccant dehumidification, and evaporative cooling for humid climates

The chimney effect for driving passively building ventilation is effective in dry and moderate climates to introduce cool fresh air into the space. However, its application in hot humid climates is limited due to the high energy demands associated with dehumidifying and cooling outdoor air. Thus, a novel energy-efficient assistive system is proposed integrating a chimney-driven ventilation with liquid desiccant dehumidification membrane loop and indirect evaporative cooling. This system leverages natural buoyancy to supply ventilation airflow and uses potassium formate loops through semi-permeable membranes for effective dehumidification. The objective is to dehumidify and cool the induced outdoor air to the room conditions of 24°C and relative humidity between 40% and 60% at minimal energy consumption. Mathematical models were developed to simulate the heat and mass transfer processes in the air and liquid desiccant flows within the system components. The system was sized, and its operation was optimized using an advanced machine learning-genetic algorithm model for a typical office space in Beirut. During the summer, the chimney air flowrate ranged from 45L/s to 48L/s, and it was delivered at the target room conditions. The system saved around 350kWh of electrical energy during the summer months due to elimination of the need to treat ventilation air by room cooling system. This was equivalent to the total energy required to handle the ventilation load during the summer season and resulted in a saving of $50/month in the case study.

Design and construction of an artificial labor-division consortium for phenanthrene degradation with three-functional modules

Polycyclic Aromatic Hydrocarbons (PAHs) are highly toxic organic pollutants. Phenanthrene often serves as a model compound for studying PAHs biodegradation. In this work, we firstly engineered Escherichia coli M01 containing seven phenanthrene degradation genes and combined it with existing engineered strains E. coli M2 and M3 to form an artificial three-bacteria consortium, named M0123, which exhibited a degradation ratio of 64.66% for 100 mg/L of phenanthrene over 8 days. Subsequently, we constructed engineered Pseudomonas putida KTRL02 which could produce 928.49 mg/L rhamnolipids and integrated it with M0123, forming a four-bacteria consortium with an impressive 81.62% phenanthrene degradation ratio. Assessment of extracellular adenosine levels during the degradation process indicated high cellular energy demand in the four-bacteria consortium. Then, we introduced Bacillus subtilis RH33, a riboflavin-producing strain, as an energy-supplying bacterium, to create a five-bacteria consortium, which exhibited an 88.19% degradation ratio for phenanthrene. The NADH/NAD+ ratio in the five-bacteria consortium during the degradation process was monitored, which was consistently higher than that of the four-bacteria consortium over the eight-day period, indicating a higher overall intracellular reduction capacity. Furthermore, the five-bacteria consortium displayed good tolerance to phenanthrene, even achieving a degradation ratio of 79.38% for 500 mg/L of phenanthrene. This study demonstrates that designing and constructing artificial consortia from the functional perspective and various angles can effectively enhance the degradation of phenanthrene after the addition of the energy-supplying bacterium. This study demonstrates that designing and constructing artificial labor-division consortia from the functional perspective and various angles can effectively enhance the degradation of phenanthrene.

Nicotinamide Mononucleotide (NMN) Ameliorates Free Fatty Acid-Induced Pancreatic β-Cell Dysfunction via the NAD+/AMPK/SIRT1/HIF-1α Pathway.

As the sole producers of insulin under physiological conditions, the normal functioning of pancreatic β cells is crucial for maintaining glucose homeostasis in the body. Due to the high oxygen and energy demands required for insulin secretion, hypoxia has been shown to play a critical role in pancreatic β-cell dysfunction. Lipid metabolism abnormalities, a common metabolic feature in type 2 diabetic patients, are often accompanied by tissue hypoxia caused by metabolic overload and lead to increased free fatty acid (FFA) levels. However, the specific mechanisms underlying FFA-induced β-cell dysfunction remain unclear. Nicotinamide mononucleotide (NMN), a naturally occurring bioactive nucleotide, has garnered significant attention in recent years for its effectiveness in replenishing NAD+ and alleviating various diseases. Nevertheless, studies exploring the mechanisms through which NMN influences β-cell dysfunction remain scarce. In this study, we established an in vitro β-cell dysfunction model by treating INS-1 cells with palmitate (PA), including control, PA-treated, and PA combined with NMN or activator/inhibitor groups. Compared to the control group, cells treated with PA alone showed significantly reduced insulin secretion capacity and decreased expression of proteins related to the NAD+/AMPK/SIRT1/HIF-1α pathway. In contrast, NMN supplementation significantly restored the expression of pathway-related proteins by activating NAD+ and effectively improved insulin secretion. Results obtained using HIF-1α and AMPK inhibitors/activators further supported these findings. In conclusion, our study demonstrates that NMN reversed the PA-induced downregulation of the NAD+/AMPK/SIRT1/HIF-1α pathway, thereby alleviating β-cell dysfunction. Our study investigated the mechanisms underlying PA-induced β-cell dysfunction, examined how NMN mitigates this dysfunction and offered new insights into the therapeutic potential of NMN for treating β-cell dysfunction and T2DM.

Computational analysis of 1T-MoS2: Probing the interplay of layer-dependent electronic structure, quantum capacitance, charge density and mechanical properties

To meet the high energy demand of society, a conversion to renewable energy sources has become essential and energy should be appropriately stored for future use. This has led to the development of energy-storing devices such as supercapacitors (SCs). To enhance capacitive behavior, the concept of quantum capacitance (CQ) is unveiled, which results from the confinement of electrons in their energy states. In this work, 1T phase of MoS2 is studied as it has received a lot of attention because of its wide applications in the energy storage devices and electronics. Here, the electronic structure, CQ and surface charge density (σ) of one, two and three-layered structures of 1T phase is studied using Density Functional Theory. No bandgap is obtained in the Density of States (DOS) and the bands plot of 1T structure indicates their metallic character and the DOS is continuous in all three layers. The CQ of three-layered structure dominates over the other two layers throughout the potential window. The larger CQ and σ values are obtained as 1718.06 μF cm−2 and -1299.50 μC cm−2 for three-layered structure at −0.27 V and −1 V respectively. For analyzing the mechanical strength, Young's modulus is evaluated for optimized structure by applying uni-axial strain. The value is obtained as 177.37 GPa, which is a measure of elastic deformation behavior. The results suggest that the capacitive performance of 1T MoS2 for SC applications is better and it can function as flexible cathode material for asymmetric SC applications.

Rancang Bangun Cooler Box Portable Menggunakan Peltier

Technological developments and modern industrial needs increasingly demand high energy efficiency in refrigeration machine operations. In this context, the development of a more efficient cooling machine control system is very necessary. Portable cooler boxes using Thermoelectric Cooler (TEC) technology are an innovation to improve the quality and durability of fish caught by fishermen in Surabaya. This research aims to design and test a cooler box that can maintain low temperatures for a long time. This research method uses experimental methods, a series of tools and uses two test plans, namely: static and dynamic testing. The components used are three Peltier elements supported by a 12V 54A power supply, a 10K NTC temperature sensor, and a passive thermal regulator heatsink with fan. Precision testing data on the comparison sensor (thermodigital), obtained an average value of 3.75%. The error value is still categorized as a safe difference value and the tool works according to its function. Test data shows that the Cooler box can maintain a temperature between 5°C to 10°C, this temperature is ideal for slowing down the process of fish spoilage. Testing was carried out by integrating an Arduino Nano for real-time temperature monitoring which is displayed on the LCD and stored on a MicroSD. Test results show that this cooling system is effective in maintaining a stable temperature under various conditions of use, with an electrical energy consumption of 3111.38Wh per 6 hours.

Impact of the Location and Energy Carriers Used on Greenhouse Gas Emissions from a Building

The growth in population increases greenhouse gas (GHG) emissions into the environment. High GHG emissions are attributed to meat production, due to its high energy demand. The largest carbon footprint in the production of poultry meat is generated by combustion. This paper deals with the problem of greenhouse gas emissions (total dust, CO, CO2, NOx, SOx and benzo(a)pyrene) resulting from the generation of energy for heating broiler houses located in different locations in Europe. The study includes continuous measurements of selected microclimate parameters: temperature and relative humidity inside and outside the building, floor temperature, wind speed and direction, and solar radiation intensity. Validation and calibration of the model, emission calculations, and analysis of the obtained results were conducted. Eighteen design variants were assumed, differentiated by the heating fuel used (hard coal, fuel oil, gaseous fuels), material and construction solutions for the floor and the location of the facility. The analysis showed that CO2 emissions for a facility located in northern Europe are 123,153 kg higher compared to the same building located in southern Europe. In addition, increasing the floor’s thermal resistance by 3.69 m2·K·W−1 reduced harmful gas emissions by an average of 5.7% for each of the locations analysed.

A Systematic Review of Expert Systems for Improving Energy Efficiency in the Manufacturing Industry

Against the backdrop of the European Union’s commitment to achieve climate neutrality by 2050, efforts to improve energy efficiency are being intensified. The manufacturing industry is a key focal point of these endeavors due to its high final electrical energy demand while simultaneously facing a growing shortage of skilled workers crucial for meeting established goals. Expert systems (ESs) offer the chance to overcome this challenge by automatically identifying potential energy efficiency improvements, thereby playing a significant role in reducing electricity consumption. This paper systematically reviews state-of-the-art ES approaches aimed at improving energy efficiency in industry with a focus on manufacturing. The literature search yields 1668 results, of which 62 articles published between 1987 and 2024 are analyzed in depth. These publications are classified according to the system boundary, manufacturing type, application perspective, application purpose, ES type, and industry. Furthermore, we examine the structure, implementation, utilization, and development of ESs in this context. Through this analysis, this review reveals research gaps, pointing toward promising topics for future research.