Integrated energy systems (IESs) can easily accommodate renewable energy resources (RESs) and improve the utilization efficiency of fossil energy by integrating various energy production, conversion, and storage technologies. However, the coupled multi-energy flows and the uncertainty of RESs bring challenges regarding optimal scheduling. Therefore, this study proposes an energy bus-based matrix-modeling method and a coordinated scheduling strategy for the IES. The matrix-modeling method can be used to formulate the steady- and transient-state balances of the multi-energy flows, and the transient model can clearly express the multi-time-scale characteristics of the different energy flows. The model parameters are fitted with data from experiments and the literature. To address the inherent randomness of the RESs and loads, a coordinated scheduling strategy is designed that contains two components: day-ahead optimization and rolling optimization. Day-ahead optimization uses the system steady-state model and multiple scenarios from the RES and load forecast data to minimize the operation cost while rolling optimization is based on the system’s transient-state model and aims to achieve the optimal real-time scheduling of the energy flows. Finally, a case study is conducted to verify the advantages and effectiveness of the proposed model and optimization method. The results show that stochastic optimization reduces the total daily cost by 1.48% compared to deterministic optimization when considering the prediction errors associated with the RESs and loads, highlighting the stronger adaptability of stochastic optimization to prediction errors. Moreover, rolling optimization based on the system’s transient-state model can reduce the errors between day-ahead scheduling and rolling correction. Full article

As a major emitter of CO₂, China needs to take responsibility for slowing down global warming. In this paper, the potential carbon emission intensity of provinces is firstly calculated using the non-radial directional distance function under the group- and meta-frontier techniques, and then six scenarios based on two factors (economic development and carbon intensity) are set up to estimate the emission reduction potential of China and each province. Considering the goal of carbon neutrality, the calculation of CO₂ emission reduction potential quantifies the amount of emissions that can be reduced and the amount of emissions that should be balanced. Additionally, the degree of difficulty in achieving abatement potential is also calculated. The findings are as follows: First, assuming that the economic growth rate is reduced to 4.4% (achieving the second “100-year goal”) and each province adopts the most advanced low-carbon technologies, China could reduce carbon emissions by 5970.56 Mt compared to 2019 levels. To achieve net-zero emissions, the remaining 3824.2 Mt of carbon emissions should be removed by carbon reduction technologies. Second, the effect of slowing down economic growth and decreasing carbon intensity varies greatly among provinces. Hebei and Shandong should be prioritized as they have the greatest potential for emission reductions under both scenarios. Third, it is more difficult for Beijing, Shanghai, Hubei, Hunan, Inner Mongolia Autonomous Region, Chongqing, and Sichuan to achieve the abatement potential and they require more effort to reduce the same amount of carbon emissions compared to other provinces. The study provides a reference for achieving carbon neutrality and helps provinces to develop differentiated emission reduction strategies. Full article

Laterality preferences are intrinsic in most physical activities, and ice hockey is one domain wherein these preferences might influence performance. Biomechanical laterality between dominant and nondominant (or preferred and nonpreferred) limbs is believed to be an advantageous attribute that is linked with skilled performance. Yet little is known about the implications of motor asymmetries for skilled performers in dynamic, time-constrained, team-based activities in an off-ice environment. This can be extended to when player position is considered, notably for those playing in a defensive or an offensive position. In this study, fourteen semi-professional collegiate male ice hockey players (age: 21.87 ± 2.98 years; BMI: 25.26 ± 3.21 kg/m) performed a randomized repeated 15 m sprint-change of direction task. Assessments of lower limb laterality were carried out as participants commenced the 15 m sprint change of direction task in both a right and left foot rear setback position. Biomechanical laterality between right and left rear foot setback positions was inferred by an ActiGraph GTx3 triaxial accelerometer that was located on the participants’ spinous process, representing the trunk centre of mass (CoM). Overall, ANOVA results indicated significant differences across all sprint split times between the right and left foot rear setback positions, with times significantly quicker when players commenced in a right rear foot setback position (p < 0.001). ANOVA revealed significant differences in trunk CoM acceleration between in a right and left rear setback position, specifically during the initial 0–10 m sprint split, with offensive players observed to have lesser trunk anteroposterior and vertical CoM acceleration (p = 0.05) and during the final 5 m sprint split (p = 0.002, d = 0.7), despite overall smaller effect sizes seen in the left foot rear setback position. It appears that starting with the foot in a right rear setback position results in quicker 15 m performance times and concurrent lower magnitudes of trunk CoM acceleration. Although we demonstrated that offensive players were quicker and displayed less trunk CoM acceleration, we recommend that future studies use a greater number of participants for inter-limb symmetry in these movement tests. Full article

This study examines the strategic use of life cycle cost analyses (LCCAs) in the management and conservation of heritage sites, emphasizing the need for comprehensive financial planning. With an increasing number of heritage sites showing signs of deterioration, our aim was to improve the sustainability and effectiveness of restoration practices. We used dynamic life cycle costing methods and developed the MONUREV software V2 to simulate different restoration scenarios, providing accurate, data-driven projections for maintaining structural, functional and aesthetic integrity. The field research involved testing these methods through case studies of heritage buildings in the Czech Republic, focusing on holistic cost management from initial analysis to practical application. The results showed that LCC analysis can significantly assist in making informed decisions, balancing economic and cultural values, and ensuring long-term conservation outcomes. This study concludes that the integration of a detailed LCC analysis into heritage conservation strategies represents a methodological advance that can significantly improve the economic and operational planning of the maintenance of heritage buildings, thereby ensuring their preservation for future generations. Full article

Introduction: The role of stereotactic body radiation therapy (SBRT) as a locally effective therapeutic approach for liver oligometastases from tumors of various origin is well established. We investigated the role of robotic SBRT (rSBRT) treatment on oligometastatic patients with liver lesions. Material and Methods: This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The PubMed and Scopus databases were accessed by two independent investigators concerning robotic rSBRT for liver metastases, up to 3 October 2023. Results: In total, 15 studies, including 646 patients with 847 lesions that underwent rSBRT, were included in our systematic review. Complete response (CR) after rSBRT was achieved in 40.5% (95% CI, 36.66–44.46%), partial response (PR) in 19.01% (95% CI, 16.07–22.33%), whereas stable disease (SD) was recorded in 14.38% (95% CI, 11.8–17.41%) and progressive disease (PD) in 13.22% (95% CI, 10.74–16.17%) of patients. Progression-free survival (PFS) rates at 12 and 24 months were estimated at 61.49% (95% CI, 57.01–65.78%) and 32.55% (95% CI, 28.47–36.92%), respectively, while the overall survival (OS) rates at 12 and 24 months were estimated at 58.59% (95% CI, 53.67–63.33%) and 44.19% (95% CI, 39.38–49.12%), respectively. Grade 1 toxicity was reported in 13.81% (95% CI, 11.01–17.18%), Grade 2 toxicity in 5.57% (95% CI, 3.82–8.01%), and Grade 3 toxicity in 2.27% (955 CI, 1.22–4.07%) of included patients. Conclusions: rSBRT represents a promising method achieving local control with minimal toxicity in a significant proportion of patients. Further studies are needed to evaluate the role of rSBRT in the management of metastatic liver lesions. Full article

Due to the convenience of online grocery apps and home delivery, online grocery shopping has become popular in recent years. Globally, consumer behavior has significantly changed the consumption and purchase patterns of online grocery shopping. This study aimed to develop an efficient model for online grocery order fulfillment that both reduces costs and increases supply chain efficiency and sustainability. This study first aimed to develop the current picking model by adopting real-world data from a store in Riyadh, Saudi Arabia. Subsequently, four proposed models were developed to improve the efficiency and sustainability of the online grocery order fulfillment process. The results show a significant improvement in all models over the current picking model. The percentage improvements in fulfillment time per product are as follows: single order picking—8.33%; batch order picking—6.78%; zone order picking—3.08%; and hybrid order picking—13.20%, which combines zone and batch order picking. Retailers and online grocery apps could adopt these models to increase efficiency and sustainability. Also, these models have great potential for future research and improvement by optimizing product placement, in addition to picking methods and picking routes, which are the focus of this study. Full article

A deep convolution network that expands on the architecture of the faster R-CNN network is proposed. The expansion includes adapting unsupervised classification with multiple backbone networks to improve the Region Proposal Network in order to improve accuracy and sensitivity in detecting minute changes in images. The efficiency of the proposed architecture is investigated by applying it to the detection of cancerous lung tumors in CT (computed tomography) images. This investigation used a total of 888 images from the LUNA16 dataset, which contains CT images of both cancerous and non-cancerous tumors of various sizes. These images are divided into 80% and 20%, which are used for training and testing, respectively. The result of the investigation through the experiment is that the proposed deep-learning architecture could achieve an accuracy rate of 95.32%, a precision rate of 94.63%, a specificity of 94.84%, and a high sensitivity of 96.23% using the LUNA16 images. The result shows an improvement compared to a reported accuracy of 93.6% from a previous study using the same dataset. Full article

Investors are increasingly relying on Environmental, Social, and Governance (ESG) indexes to obtain a third-party assessment of corporate sustainability performance. Various ESG indexes are, therefore, released by prominent rating agencies, including MSCI, Sustainalytics, Refinitiv, etc. However, existing ESG indexes overvalue the usage of massive ESG metrics while ignoring various ESG disclosure levels, leading to critical issues such as limited company coverage, inflexible ESG framework, and obscure assessment processes. This paper proposes a novel Dual ESG Index (DESGI) model using blockchain technology to provide a flexible and transparent corporate sustainability assessment. Firstly, the DESGI model is developed by analogy to the rationale and concepts of the academic credit system due to its advantages of scalability and flexibility. Secondly, blockchain is used to build a transparent environment for ESG assessment. Thirdly, the smart contract and crypto token, as the core blockchain constructs, are used to achieve the dual-dimensional ESG depth and width assessment using ESG GPA and ESG credit, respectively. Finally, a case study is carried out to validate the DESGI by using real-life ESG data and comparing it with four existing ESG indexes. Several managerial implications are also found: (1) DESGI can expand the scope of companies evaluated by ESG criteria regardless of company size or scale; (2) DESGI provides a good potential to fight against greenwashing through the blockchain-based traceability; (3) DESGI can identify the ESG elites who disclose fewer ESG metrics but with excellent ESG performances, which can hardly be achieved using traditional ESG indexes. Full article

In the era of Innovation 3.0, more and more enterprises are working together to build an innovation ecosystem to achieve value creation. The various participants in the innovation ecosystem promote resource aggregation and integration through cross boundary collaboration, jointly creating the value of the ecosystem. Value co-creation has become the core goal pursued by the participants in the innovation ecosystem. As an innovative participant in the innovation ecosystem, it is particularly necessary for enterprises to explore the formation mechanism of value co-creation from the perspective of enterprise knowledge characteristics. This article analyzes the value co-creation mechanism of innovation ecosystems from the perspective of including internal knowledge bases and external relationships. Based on the dimension of knowledge element relationships, a theoretical model is constructed to investigate the impact of enterprise knowledge element relationships on value co-creation in innovation ecosystems and explore the mediating role of knowledge synergy and the moderating role of innovation ecosystem normativity. The relationships are modeled based on survey data collected from 427 Chinese companies, and multiple regression analysis and bootstrap methods are used to empirically test the hypotheses. The research results show that different dimensions of knowledge element relationships have different impacts on value co-creation. Knowledge element substitution negatively affects value co-creation, while knowledge combination diversity positively affects value co-creation. However, there is an inverted U-shaped relationship between knowledge element complementarity and value co-creation. Knowledge synergy partially mediates the relationship between knowledge element relationships and value co-creation, and innovation ecosystem normativity has a two-stage moderating effect on the path from knowledge element relationships to knowledge synergy to value co-creation. This article enriches the research content of knowledge management in innovation ecosystems, guides enterprises in the innovation ecosystem to reasonably construct their own knowledge systems, and promotes the formation of innovation ecosystem norms, thus promoting the development of value co-creation activities. Full article

Indole phytoalexins, found in economically significant Cruciferae family plants, are synthesized in response to pathogen attacks or stress, serving as crucial components of plant defense mechanisms against bacterial and fungal infections. Furthermore, recent research indicates that these compounds hold promise for improving human health, particularly in terms of potential anticancer effects that have been observed in various studies. Since our last comprehensive overview in 2016 focusing on the antiproliferative effects of these substances, brassinin and camalexin have been the most extensively studied. This review analyses the multifaceted pharmacological effects of brassinin and camalexin, highlighting their anticancer potential. In this article, we also provide an overview of the antiproliferative activity of new synthetic analogs of indole phytoalexins, which were synthesized and tested at our university with the aim of enhancing efficacy compared to the parent compound. Full article

The Metaverse promises to change our lives and how we usually interact with the world. However, it can only evolve with technological development and entertainment engagement advances. To investigate more leads regarding this concept, we have a main search question: How are the Metaverse, gaming, and digital twins represented in Academia? To answer it, we need to verify and determine how the Metaverse is defined, how gaming, as an entertainment industry, is represented, and how Digital Twins are defined by scientific knowledge. It will also be important to analyze how these concepts are intercorrelated. Here, we present a documental study—meta-analysis—of the most relevant indexed scientific papers published in the last ten years, according to predefined inclusion and exclusion criteria. Leximancer software will help us determine the main concepts and themes extracted from these articles—namely from the Keywords, Abstracts, Methodologies, and Conclusions sections. This study allows us to understand how these concepts are perceived, contribute to a scientific discussion, and give suggestions for future research and new leads on approaching these concepts. Full article

The quality of pork is significantly impacted by intramuscular fat (IMF). However, the regulatory mechanism of IMF depositions remains unclear. We performed whole-transcriptome sequencing of the longissimus dorsi muscle (IMF) from the high (5.1 ± 0.08) and low (2.9 ± 0.51) IMF groups (%) to elucidate potential mechanisms. In summary, 285 differentially expressed genes (DEGs), 14 differentially expressed miRNAs (DEMIs), 83 differentially expressed lncRNAs (DELs), and 79 differentially expressed circRNAs (DECs) were identified. DEGs were widely associated with IMF deposition and liposome differentiation. Furthermore, competing endogenous RNA (ceRNA) regulatory networks were constructed through co-differential expression analyses, which included circRNA-miRNA-mRNA (containing 6 DEMIs, 6 DEGs, 47 DECs) and lncRNA-miRNA-mRNA (containing 6 DEMIs, 6 DEGs, 36 DELs) regulatory networks. The circRNAs sus-TRPM7_0005, sus-MTUS1_0004, the lncRNAs SMSTRG.4269.1, and MSTRG.7983.2 regulate the expression of six lipid metabolism-related target genes, including PLCB1, BAD, and GADD45G, through the binding sites of 2-4068, miR-7134-3p, and miR-190a. For instance, MSTRG.4269.1 regulates its targets PLCB1 and BAD via miRNA 2_4068. Meanwhile, sus-TRPM7_0005 controls its target LRP5 through ssc-miR-7134-3P. These findings indicate molecular regulatory networks that could potentially be applied for the marker-assisted selection of IMF to enhance pork quality. Full article

The heat treatment of aluminum alloys is very important in industries where low weight in combination with high wear resistance, good strength, and hardness are important. However, depending on their chemical composition, aluminum alloys are subjected to different mechanical and thermal treatments to achieve the most favorable properties. In this study, an Al-Zn-Mg alloy was heat-treated including solution annealing at 490 °C for 1 h with subsequent artificial aging at 130, 160, and 190 °C for 1, 5, and 9 h. The hardness (HV1) and abrasive wear resistance with three different abrasive grain sizes were measured for all samples. The highest hardness was measured for the samples artificially aged at 130 °C/5 h, 227 HV1, while the lowest hardness was measured for the samples aged at 190 °C/9 h. The highest and the lowest wear resistance was also observed for the same state, i.e., artificially aged at 130 °C/5 h and 190 °C/9 h, respectively. The critical abrasive grain size was detected for some samples, where a decrease in wear rate was observed with an increase in the abrasive grain size from the medium value to the largest. The Response Surface Methodology (RSM) was applied to demonstrate the influence of the input parameters on the material wear rate. Full article

Pertussis continues to be a highly contagious respiratory infection, especially in children, with cyclical peaks of disease spread every three to five years. Here, we report relevant cases of B. pertussis infection between August 2023 and January 2024, and compare them with B. pertussis prevalence in pediatric patients admitted to the Reference Italian Pediatric Hospital, located in Rome, from January 2015 to July 2023. A total of 5464 tests for B. pertussis were performed during the study period, and 6.9% were positive. At the time of the COVID-19 pandemic, there was a sharp decrease in the presence of B. pertussis, which reappeared only in August 2023, recording five new cases. All five children presented with paroxysmal cough 5 to 10 days before admission. Four patients had other mild respiratory symptoms and moderate B. pertussis DNA levels (Ct mean: 26). Only one child, with very high B. pertussis DNA levels (Ct: 9), presented with severe respiratory failure. The patients with mild/moderate infection achieved clinical recovery while the patient with the severe manifestation died of cardiac arrest. These observations highlight the reemergence of pertussis even in vaccinated countries and its association with morbidity and mortality especially in young children. This emphasizes the importance of rapid diagnosis to immediately implement appropriate treatment and monitoring of immune status. Full article

In the development of intelligent mines, unmanned driving transportation has emerged as a key technology to reduce human involvement and enable unmanned operations. The operation of unmanned vehicles in mining environments relies on remote operation, which necessitates the low-latency transmission of high-definition video data across multiple channels for comprehensive monitoring and precise remote control. To address the challenges associated with unmanned driving in mines, we propose a comprehensive scheme that leverages the capabilities of 5G super uplink, edge collaborative computing, and advanced video transmission strategies. This approach utilizes dual-frequency bands, specifically 3.5 GHz and 2.1 GHz, within the 5G super uplink framework to establish an infrastructure designed for high-bandwidth and low-latency information transmission, crucial for real-time autonomous operations. To overcome limitations due to computational resources at terminal devices, our scheme incorporates task offloading and edge computing methodologies to effectively reduce latency and enhance decision-making speed for real-time autonomous activities. Additionally, to consolidate the benefits of low latency, we implement several video transmission strategies, such as optimized network usage, service-specific wireless channel identification, and dynamic frame allocation. An experimental evaluation demonstrates that our approach achieves an uplink peak rate of 418.5 Mbps with an average latency of 18.3 ms during the parallel transmission of seven channels of 4K video, meeting the stringent requirements for remote control of unmanned mining vehicles. Full article

We analyze the two classic methods for chirped Integrated Bragg Gratings (IBGs) in Silicon-on-Insulator technology using the transfer matrix method based on the effective refractive index (n_eff) technique, which translates the geometry of an IBG into a matrix of n_eff depending on the wavelength. We also implement a procedure that allows engineering of the chirped IBG parameters, given a required bandwidth (BW) and group delay (GD). Finally, a complementary method for designing chirped IBG is proposed, showing a significant improvement in the bandwidth of the device or a moderation in the variation of the geometrical parameters of the grating. Full article

A squaramide-based organocatalyst for asymmetric Michael reactions has been tested as a chiral solvating agent (CSA) for 26 carboxylic acids and camphorsulfonic acid, encompassing amino acid derivatives, mandelic acid, as well as some of its analogs, propionic acids like profens (ketoprofen and ibuprofen), butanoic acids and others. In many cases remarkably high enantiodifferentiations at ¹H, ¹³C and ¹⁹F nuclei were observed. The interaction likely involves a proton transfer from the acidic substrates to the tertiary amine sites of the organocatalyst, thus allowing for pre-solubilization of the organocatalyst (when a chloroform solution of the substrate is employed) or the simultaneous solubilization of both the catalyst and the substrate. DOSY experiments were employed to evaluate whether the catalyst–substrate ionic adduct was a tight one or not. ROESY experiments were employed to investigate the role of the squaramide unit in the adduct formation. A mechanism of interaction was proposed in accordance with the literature data. Full article

Hard ceramic coatings were successfully prepared on the surface of ZM5 magnesium alloy by micro-arc oxidation (MAO) technology in silicate and aluminate electrolytes, respectively. The optimization of hard ceramic coatings prepared in these electrolyte systems was investigated through an orthogonal experimental design. The microstructure, elemental composition, phase composition, and tribological properties of the coatings were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and tribological testing equipment. The results show that the growth of the hard ceramic coatings is significantly influenced by the different electrolyte systems. Coatings prepared from both systems have shown good wear resistance, with the aluminate electrolyte system being superior to the silicate system in performance. The optimized formulation for the silicate electrolyte solution has been determined to be sodium silicate at 8 g/L, sodium dihydrogen phosphate at 0.2 g/L, sodium tetraborate at 2 g/L, and potassium hydroxide at 1 g/L. The optimized formulation for the aluminate electrolyte solution consists of sodium aluminate at 5 g/L, sodium fluoride at 3 g/L, sodium citrate at 3 g/L, and sodium hydroxide at 0.5 g/L. Full article

It is of great significance to explore the molecular mechanism of gametophytic sexual reproduction in the genetic improvement and breeding of tea plants [Camellia sinensis (L.) O. Kuntze]. Imported beta family members (IMBs) are a class of widely distributed nucleoplasmic transport receptor proteins in eukaryotes, affecting plant development and reproduction, and participating in flowering time and sexual reproduction. Still missing, though, is a thorough examination of IMB members in tea plants. Here, seven members of the IMB gene family were screened by a genome-wide investigation in tea plants. These members were scattered unevenly throughout five chromosomes. All of them contained the conserved KAP95 and HEAT Repeat domains. Additionally, the promoter regions of CsIMBs harbored cis-acting elements associated with plant hormones, light, and abiotic stress responses. In order to further confirm the function of CsIMBs in the sexual reproduction of tea plants, the expression patterns of CsIMBs in different flower development stages and the ovary (before and after pollination) were analyzed. The expression results highlighted that CsIMBs were related to the fertility and fruiting of tea plants. Furthermore, five of the seven CsIMBs (CsIMB1a, CsIMB1b, CsIMB2, CsIMB3a, and CsIMB3b) were found to be localized in the nucleus revealed by subcellular localization analysis. These results offer a comprehensive characterization of IMB genes as well as insights into the potential roles of CsIMBs participating in the gametophytic sexual reproduction of C. sinensis. Full article

This research develops an innovative framework for accelerating Conjugate Heat Transfer (CHT) simulations within squared heated cavities through the application of Graphics Processing Units (GPUs). Although leveraging GPUs for computational speed improvements is well recognized, this study distinguishes itself by formulating a tailored optimization strategy utilizing the CUDA-C programming language. This approach is specifically designed to tackle the inherent challenges of modeling squared cavity configurations in thermal simulations. Comparative performance evaluations reveal that our GPU-accelerated framework reduces computation times by up to 99.7% relative to traditional mono-core CPU processing. More importantly, it demonstrates an increase in accuracy in heat transfer predictions compared to existing CPU-based models. These results highlight not only the technical feasibility but also the substantial enhancements in simulation efficiency and accuracy, which are crucial for critical engineering applications such as aerospace component design, electronic device cooling, and energy system optimization. By advancing GPU computational techniques, this work contributes significantly to the field of thermal management, offering a potential for broader application and paving the way for more efficient, sustainable engineering solutions. Full article

The aim of this study is to compare the dental profiles of Brazilian patients with rare genetic skeletal disorders and normotypical patients. A cross-sectional study was carried out with 210 individuals aged between 2 and 54 years old [105 with rare diseases (Mucopolysaccharidosis/MPS n = 27 and Osteogenesis Imperfecta/OI n = 78) and 105 without rare diseases] and their parents/caregivers. The parents/caregivers answered a questionnaire about individual aspects of their child and the dental profile was identified from questions related to dental history and the presence/absence of dental problems. The patients’ oral cavity was also examined by three examiners for dental caries, malocclusion, gingivitis, and dental anomalies. The average age of individuals with a rare disease was 14.1 years (±12.2) and the median was 9.5 years. Participants who had already used the public health system (SUS) dental care services had a 2.24 times higher chance of belonging to the group with a rare disease (OR = 2.24; 95% CI: 1.07–4.89). Patients with rare diseases are 14.86 times more likely to have difficulty receiving dental treatment (OR = 14.86; 95% CI: 5.96–27.03) and 10.38 times more likely to have one or more dental problems (OR = 10.38; 95% CI: 1.95–35.17). Individuals with rare disorders have a greater history of difficulty in accessing dental treatment, using the SUS, and were diagnosed with more dental problems compared to normotypical individuals. Full article

Background and Objectives: Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the quality of life of patients worldwide. Comorbidities such as chronic kidney disease (CKD), arterial hypertension, and diabetes mellitus (DM) are common among HF patients, as they share similar risk factors. This study aimed to identify the prognostic significance of multiple factors and their correlation with disease prognosis and outcomes in a Jordanian cohort. Materials and Methods: Data from the Jordanian Heart Failure Registry (JoHFR) were analyzed, encompassing medical records from acute and chronic HF patients attending public and private cardiology clinics and hospitals across Jordan. An online form was utilized for data collection, focusing on three kidney function tests, estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), and creatinine levels, with the eGFR calculated using the Cockcroft–Gault formula. We also built six machine learning models to predict mortality in our cohort. Results: From the JoHFR, 2151 HF patients were included, with 644, 1799, and 1927 records analyzed for eGFR, BUN, and creatinine levels, respectively. Age negatively impacted all measures (p ≤ 0.001), while smokers surprisingly showed better results than non-smokers (p ≤ 0.001). Males had more normal eGFR levels compared to females (p = 0.002). Comorbidities such as hypertension, diabetes, arrhythmias, and implanted devices were inversely related to eGFR (all with p-values <0.05). Higher BUN levels were associated with chronic HF, dyslipidemia, and ASCVD (p ≤ 0.001). Higher creatinine levels were linked to hypertension, diabetes, dyslipidemia, arrhythmias, and previous HF history (all with p-values <0.05). Low eGFR levels were associated with increased mechanical ventilation needs (p = 0.049) and mortality (p ≤ 0.001), while BUN levels did not significantly affect these outcomes. Machine learning analysis employing the Random Forest Classifier revealed that length of hospital stay and creatinine >115 were the most significant predictors of mortality. The classifier achieved an accuracy of 90.02% with an AUC of 80.51%, indicating its efficacy in predictive modeling. Conclusions: This study reveals the intricate relationship among kidney function tests, comorbidities, and clinical outcomes in HF patients in Jordan, highlighting the importance of kidney function as a predictive tool. Integrating machine learning models into clinical practice may enhance the predictive accuracy of patient outcomes, thereby supporting a more personalized approach to managing HF and related kidney dysfunction. Further research is necessary to validate these findings and to develop innovative treatment strategies for the CKD population within the HF cohort. Full article