Essential Criteria Research Articles

Dynamic Price Application to Prevent Financial Losses to Hospitals Based on Machine Learning Algorithms.

Hospitals that are considered non-profit take into consideration not to make any losses other than seeking profit. A model that ensures that hospital price policies are variable due to hospital revenues depending on patients with appointments is presented in this study. A dynamic pricing approach is presented to prevent patients who have an appointment but do not show up to the hospital from causing financial loss to the hospital. The research leverages three distinct machine learning (ML) algorithms, namely Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB), to analyze the appointment status of 1073 patients across nine different departments in a hospital. A mathematical formula has been developed to apply the penalty fee to evaluate the reappointment situations of the same patients in the first 100 days and the gaps in the appointment system, considering the estimated patient appointment statuses. Average penalty cost rates were calculated based on the ML algorithms used to determine the penalty costs patients will face if they do not show up, such as 22.87% for RF, 19.47% for GB, and 14.28% for AB. As a result, this study provides essential criteria that can help hospital management better understand the potential financial impact of patients missing appointments and can be considered when choosing between these algorithms.

Lung Infection Detection via CT Images and Transfer Learning Techniques in Deep Learning

Healthcare systems are battling the global coronavirus epidemic with limited resources, requiring early diagnosis and enhanced tools for pandemic prevention. The computer can aid in diagnosis via computed tomography images like PCR. Deep learning and machine learning are popular methods, and their main contributions are COVID-19 detection and prediction. This work aimed to develop an AI-based early detection strategy for COVID-19 based on computed tomography images. The model was trained and tested using a dataset that includes CT images. The SARS-COV-2 dataset contains 2482 CT images of 210 patients from publicly available sources. The modified model demonstrated encouraging outcomes by greatly enhancing the sensitivity measure (95.82±1.75), which is an essential criterion for accurately detecting instances of COVID-19 infection. In addition, the model generated higher values for the accuracy metric (91.67±1.68), the specificity (88.08±3.72), the precision metric (87.51±3.27), the F1_score (91.43±1.55), and the area under the curve (91.98±1.55). Deep learning techniques significantly facilitate the early detection of COVID-19. Its use has the potential to improve clinical doctors' readiness and the management of pandemics.

SMILEY-assistive application to support social and emotional skills in SPCD individuals.

According to the available studies, mobile applications have provided significant support in improving the diverse skills of special individuals with social pragmatic communication disorder (SPCD). Over the last decade, SPCD has affected 8 to 11% of individuals, and therapy sessions cost between $50 and $150 per hour. This preliminary study aims to develop an interactive, user-friendly intervention to enhance social and emotional interaction skills in individuals with SPCD. The proposed intervention is an Android application that enhances social and emotional interaction skills. This pilot study involved 29 human subjects aged 7-13 years with pragmatic communication deficits. In a randomized controlled trial, the intervention was developed and implemented with consideration of caregiver and professional requirements. The improvement was analyzed using standard scales, including the Social Communication Questionnaire (SCQ) and the Social Communication Disorder Scale (SCDS). Moreover, the outcomes were examined through statistical parameters (mean, standard deviation) and tests (t-test). The intervention significantly improved the social and emotional skills of individuals with deficits. Before using the intervention, the identified statistical values for SCQ (mean = 6.48 and standard deviation = 3.37) and SCDS (mean = 8.17 and standard deviation = 4.79). However, after using the intervention, values for SCQ (mean = 8.24 and standard deviation = 3.95) and SCDS (mean = 9.48 and standard deviation = 4.72) were improved in comparison to the before-intervention outcome. The evaluation of the t-scores and p-values indicates that there has been significant improvement in the performance of individuals after the successful completion of the intervention. The proposed and applied intervention resulted in a significant impact in terms of improvement in social and emotional skills. The study concluded that it allows individuals to practice social and emotional interaction skills in a structured, controlled, and interactive environment. The proposed intervention has been found acceptable as per the reviews of caregivers and professionals, based on essential criteria including user experience, usability, interactive nature, reliability, and creditability.

Criteria for Building Residential Arrangement Models on the Coastal Island System of Vietnam

This research marks a significant milestone by proposing a set of comprehensive criteria for building residential arrangement models on Vietnam's coastal island system. The unique characteristics of these islands, such as their limited space and resources, pose complex challenges for population placement. Therefore, establishing the proper criteria for population placement is crucial and pivotal to ensure this area's sustainable and harmonious development. The author has meticulously derived 13 essential criteria from various data sources, including articles, project topics, field surveys, and expert consultations. These criteria are not just a theoretical framework but a practical tool to build a reasonable population arrangement model to bring sustainable, diverse, and harmonious development to the island community.

Implementing a routine and standard approach for the automatic collection of socio-economic impact observations for impact-based forecasting and warning

Globally, there are different scientific methods being developed to support the provision of Impact-based Forecasts and Warnings. Impact data is critically valuable to many of these methods enabling the development of new hazard impact models and forecasting applications, and the evaluation of these different products. However, routine and consistent approaches to collect socio-economic impact information remain challenging, with traditional approaches being labour intensive, error prone and unsustainable. This paper describes the design of an automated workflow that can collect, standardise, and harmonise impact observations from a range of sources, routinely. The workflow is a 6-step process including web scraping, Natural Language Processing (NLP) and geoparsing. The workflow enables essential criteria (i.e., date, location, types and details of the societal impacts and the hazard(s) which led to them) to be captured faster than previous manual approaches. It also allows a wider range of hazard and impact types to be collected than was previously practical to do. Testing of the workflow indicates that it could benefit from further refinement of the NLP and geoparse modules to allow for the detection of finer scale impact locations. This in turn would allow for different scales of event detection to be developed and tested. Additionally, the applicability of the workflow for different types of impact data sources such as news and social media remains to be tested. Despite the need for further refinement, this workflow represents a step change in the speed and efficiency of impact data collection within the Met Office.

From Quarry to Monument: Considering Mardin Stone (SE, Türkiye) as the Symbol of Architectural and Cultural Heritage

The cultural and architectural significance of stone becomes evident as one traces its journey from quarry to monument. Located in southeastern Türkiye, Mardin City presents an urban landscape characterized by stone-built heritage. This transforms Mardin into an open-air museum where the final stone products are exhibited. In addition to its cultural and historical significance, the present study explores the geological, physical, mechanical, mineralogical, petrographic, and chemical properties of the Mardin Stone through the samples collected from the Artuklu, Midyat and Savur districts of Mardin. The Mardin Stone is represented by two different types of limestone deposited during the Cretaceous-Eocene period, categorized as fossiliferous micritic limestone and micritic limestone. The physicomechanical and thermal characteristics suggest that the samples collected from the Artuklu district exhibit better engineering properties than those from the Midyat and Savur districts. The study mapped ancient and modern quarries, illustrating the significance of the stone extraction and crafting techniques used to produce the Mardin Stone. Additionally, it emphasized the ongoing use of stone in contemporary structures, its vital role in heritage conservation, and its export to various countries, notably for use in the Syriac diaspora churches. The evaluations demonstrate that the Mardin Stone, with its diverse architectural applications and symbolic element of the collective memory, meets the essential standards and criteria of the International Union of Geological Sciences-Heritage Stone Subcommission (IUGS-HSS) as a potential candidate for designation as Heritage Stone.

Recent decline in sperm motility among donor candidates at a sperm bank in Denmark.

Has there been variation in semen quality among men applying to be sperm donors (i.e. donor candidates) in Denmark in recent years (2017-2022)? The motile sperm concentration and total motile sperm count (TMSC) in ejaculates-both measures of sperm quality-declined by as much as 22% from 2019 to 2022. Questions remain about whether human semen quality has declined in recent years. Whilst some studies provide evidence for a decline in human semen quality, these findings have been disputed owing to potential biases in the populations studied or in the methods used to measure semen quality. Resolution of this issue has important implications for human fertility, as well as for those involved in the recruitment of sperm donors for use in medically assisted reproduction. We obtained data on the semen quality of ejaculates previously collected from 2017 to 2022 at sperm bank locations in four cities in Denmark: Aarhus, Aalborg, Copenhagen, and Odense. Our study focuses on the single semen samples provided by 6758 donor candidates aged between 18 and 45 years old to determine whether their sperm quality met a minimum criterion for them to be accepted as sperm donors. All ejaculates were analyzed within 1 hour of production. Semen volume (ml) was estimated by weight and both the concentration (106/ml) of sperm as well as the concentration of motile sperm (World Health Organization grades a and b) were measured using the same protocols and computer-assisted semen analysis system across all years at each site. Statistical analyses of the semen variables were controlled for age and donation site, as well as the average monthly high temperature when the ejaculate was produced. From 2017 to 2019, semen volume, sperm concentration, and total sperm count in the ejaculates of donor candidates increased by 2-12%. Then, from 2019 to 2022, sperm concentration and total sperm count changed by 0.1-5% from year to year, but none of those changes were statistically significant. In contrast, both motile sperm concentration and TMSC declined significantly, by 16% and 22%, respectively, between 2019 and 2022. Thus, the concentration of motile sperm in donor candidates declined from 18.4 [95% CL: 17.0, 20.0] million/ml in 2019 to 15.5 [14.4, 16.7] million/ml in 2022, and TMSC declined from 61.4 [55.8, 67.5] million per ejaculate in 2019 to 48.1 [44.1, 52.4] million in 2022. We cannot determine from the available data the causes of the decline in semen quality of donor candidates from 2019 to 2022. However, as this period coincides with lockdowns and changes in work patterns during the coronavirus disease 2019 pandemic, it is possible that changes in motile sperm concentration and TMSC were the result of changes in the lifestyles of the men whose semen was analyzed. Men providing initial semen samples at sperm banks, when applying to be sperm donors, are a useful population in which to monitor changes in human semen quality over time. Our results have implications for human fertility and the recruitment of sperm donors for medically assisted reproduction, where motile sperm concentration is an essential selection criterion because it influences fertility. We suggest that gathering health and lifestyle data on donor candidates at sperm banks might help to identify causal factors for the decline of sperm quality that could be addressed and intervention, if desired, could be personalized for each accepted donor. No external funding was obtained for this study. E.L. and A.-B.S. are employees of Cryos International. AP reports paid consultancy for Cryos International, Cytoswim Ltd, Exceed Health, and Merck Serono in the last 2 years of this study, but all monies were paid to the University of Sheffield (former employer). AP is also an unpaid trustee of the Progress Educational Trust (Charity Number 1139856). RM declares support from Cryos International to present results of this research at ESHRE 2023. None of the authors were directly involved in the collection or physical analysis of semen samples. N/A.

Green and Convenient Synthesis of Pharmaceutically Active Mono and Bis-dihydroquinazolines via a One-pot Multicomponent Reaction Under Sulfamic Acid Catalysis

Introduction: Multicomponent reactions (MCRs) and green chemistry are essential criteria for the development of efficient chemical syntheses for valuable organic compounds. Method: The design, synthesis, and development of sustainable procedures for the production of novel biological and pharmaceutical molecules have gained high importance. Herein, an environmentally benign synthesis of mono- and bis-2,3-dihydroquinazolin-4(1H)-ones as pharmaceutically active compounds was carried out in good to high yields of 80-99% within 45-120 minutes. Result: The desired products were synthesized via three-component and pseudo five-component condensations of isatoic anhydride, a primary amine (aniline or ammonium acetate), and an aldehyde/dialdehyde using sulfamic acid (20%) as a solid acidic catalyst under the solvent-free condition at 100°C. Conclusion: The easy work-up procedure, metal-free and environmentally benign catalyst, green reaction conditions for performing MCRs, and high yields of pure products are some advantages of the presented protocol.

Aggregate Boid behavior to aid in artificial autopoietic organization

Analyzing carbon-based life on earth can lead to biased inferences on the nature of life as might exist in elsewhere in the universe in alternative forms, therefore, scientists have looked into either abstracting life into constituent systems it is comprised of, or logics of life, or lists of essential criteria, or essential dynamic patterning that characterizes the living. A system-level characterization that is and referred to as a general pattern of minimal life is autopoiesis (Varela et al., 1974) including production, maintenance and replacement of required constituents for setting up and maintaining an internal environment with self/other separation that regulates and is constitutive of processes that produce the environment and components for processes that comprise this ongoing activity of self-production in ‘recursively’, i.e., in a manner that allows the organizational pattern to continually reconstitute the conditions, components and processes required for its own perpetuation. This seminal concept of an autopoiesis is instantiated in life as we know it, but might also be instantiated in different media and in unforeseen ways. Other researchers have argued life is more than autopoiesis and that it is a co-emergent property of autopoiesis and cognition. Life produces many emergent properties such as synchronization and patterns as seen in flocks and herds of different animal species. The mechanics of this synchrony displayed in flocks and herd animals has been extracted by Craig Reynolds into a generative model referred to as “Boids”. With these concepts in mind, we address the following research question: How can the synchronous maneuvers and aggregate behavior of Boids contribute to constitutive subsystems in realizing an autopoietic system? Can such a system exhibit minimal cognition? This work attempts to answer these questions with a bottom-up approach to constructing an artificial life system. We exhibit a computational model of autopoiesis and a minimal level of cognition in the sense of M. Bitbol and P. Luigi Luisi, whereby an autopoietic entity engages in active assimilation of external components as part of its activity of self-production.

Apatinib and camrelizumab plus Intravenous FOLFOX or hepatic arterial infusion chemotherapy with FOLFOX for advanced HCC: A multicenter, prospective, randomized phase III trial.

TPS4193 Background: The combination of anti-angiogenesis and immune checkpoint blockade showed promising outcomes for advanced hepatocellular carcinoma (HCC). Hepatic artery infusion chemotherapy (HAIC) combined with apatinib and camrelizumab could augment treatment efficacy in preliminary study. But HAIC has disadvantages such as technical limitations, expensive cost, impaired liver function and poor patient comfort. Results from our previous phase II trial (NCT05412589) demonstrate that the triplet treatment of Venous Infusional FOLFOX plus camrelizumab and apatinib showed inspiring antitumor activity and acceptable safety for CNLC stage Ⅲ HCC, especially in those with main portal trunk invasion (Vp4). These results encourage us to further compare the efficacy and safety of intravenous FOLFOX with apatinib and camrelizumab versus HAIC-FOLFOX with apatinib and camrelizumab as first-line treatment in advanced HCC. Methods: This multicenter, randomized, open-label, non-inferiority phase 3 study (NCT06172205) will enroll 192 patients. Essential criteria for patient inclusion encompassed: age between 18 and 75 years; a clinical diagnosis conforms to primary hepatocellular carcinoma (HCC); classification with in BCLC stage C; no prior anti-tumor treatment exposure; presence of at least one measurable tumor as per RECIST v1.1; ECOG performance status score of either 0 or 1; and a Child-Pugh A or B. Eligible patients were randomized (1:1) into two groups. Randomization is stratified by the presence of macrovascular invasion or extrahepatic metastasis (yes vs no), and baseline alpha-fetoprotein concentration (<400 ng/mL vs ≥400 ng/mL). There are 2 arms in the study: (1) Arm A: FOLFOX (oxaliplatin 85 mg/m2, leucovorin 200 mg/m2,5-fluorouracil bolus 400 mg/m2 on day 1, and 5-fluorouracil infusion 2400 mg/m2 for 46 hours; q3w; up to 6 cycles) intravenously in combination with apatinib (250 mg po qd) and camrelizumab (200 mg iv q3w). (2) Arm B: hepatic arterial infusion FOLFOX (oxaliplatin, leucovorin and 5-fluorouracil q3w; up to 6 cycles), combined with apatinib (250 mg po qd) and camrelizumab (200 mg iv q3w). The primary endpoint is 6-month progression-free survival (PFS) rate according to RECIST v1.1. Secondary outcomes encompass the Objective response rate, Disease control rate, Duration of response, PFS, Overall survival (OS), along with 12-month PFS rate, 6-month and 12-month OS rates. The additional secondary endpoints include assessment of treatment-related adverse events. With the assumption of a median 6-month PFS rate of 85% in the Arm B and 71% in the Arm A (noninferiority margin, 14%), a total of 162 patients were required under a two-sided 5% significance level and 80% power. Allowing a dropout rate of 15%, we aimed to enroll 192 patients. The trial is currently screening eligible patients. Clinical trial information: NCT06172205 .

A Smart Secure model for Detection of DDoS Malicious Traces in Integrated LEO Satellite-Terrestrial Communications

For many researchers, defense against DDoS attacks has always been a major subject of attention. Within the LEO Satellite-Terrestrial (LSTN) network field, distributed denial of service (DDoS) attacks is considered to be one of the most potentially harmful attack techniques. For the facilitation of network protection by the detection of DDoS malicious traces inside a network of satellite devices, machine learning algorithms plays a significant role. This paper uses modern machine learning approaches on a novel benchmark Satellite dataset. The STIN and NSL-KDD datasets has been used to detect network anomalies. The pre-processing of data has been performed effectively and a host of ML methods have been applied to classify the outputs into normal, regular node or untrustable /malicious node. We have evaluated the analysis results in presence of attacks as well as without presence of attacks, supervised machine learning techniques basic measurements like accuracy, True positive, False positive etc. Our proposed trust model shows better accuracy, nearby 98% and we have shown that our proposed machine learning based security model performs better to get rid of DDoS attacks on integrated LEO satellite-terrestrial networks without compromising on the packet routing efficiency. We are able to improve routing speed and improve network security against distributed denial of service (DDoS) attacks by integrating an ensemble-based trust model trained on NSL-KDD+STIN+Exata Simulated resultant dataset with ACO for routing decisions. In dynamic network scenarios, as trustworthiness is an essential criterion in route decision-making, this proposed approach signifies resilient and adaptable routing.

POLE-mutated Endometrial "Carcinosarcoma".

The molecular subtype classification of endometrial carcinomas has conceptually changed our approach to this disease. However, open questions remain about how to integrate certain histotype diagnoses with the molecular subtype. We report 2 cases with morphologic suspicion for endometrial carcinosarcoma, that still fell short of the essential criteria for diagnosing carcinosarcoma. On subsequent molecular testing pathogenic POLE mutations were detected and a descriptive diagnosis of endometrial endometrioid carcinomas, low-grade with a homologous sarcoma component was rendered. This challenges the existence of POLE-mutated "carcinosarcoma."

A Study of Employees' Willingness to Delay Retirement from an Industry Perspective

In recent years, due to China's aging population, pension insurance payment tension and other factors combined with China's specific employment situation, delayed retirement has gradually become one of the hot topics in all walks of life. The implementation of delayed retirement policy is an important task put forward by the Third and Fifth Plenary Sessions of the 18th Central Committee, and delaying the retirement age has been the general trend in China. The introduction and implementation of the policy of delayed retirement age involves the personal interests of employees in various industries, and the willingness of employees engaged in different jobs to delay retirement is an essential public opinion criterion for the introduction of the policy, and it will directly affect the specific implementation of the delayed retirement policy. For this reason, this paper will be based on the background of different industries to explore the willingness of employees to delay retirement research, will delay the implementation of the policy in different sectors of the resistance to materialization, for policy makers and business managers to provide scientific reference.

Nanocellulose/scleroglucan-enhanced robust, heat-resistant composite hydrogels for oilfield water plugging

In an oil exploitation process, hydrogel plugging agents can effectively reduce the water-oil intermixing, decrease water extraction volume, and enhance oil recovery rate. The practical applications of traditional polyacrylamide (PAM) hydrogel plugging agents in oilfield are limited by their non-biodegradability, poor mechanical performance, and inferior temperature-resistance. This work developed a mechanically stable and high-temperature-resistant composite hydrogel (STP) by incorporating biodegradable scleroglucan (Slg) and TEMPO-oxidized cellulose nanofibers (TOCN) in the PAM hydrogel. The addition of Slg conferred heat resistance to the PAM hydrogel, while TOCN reinforced the mechanical strength. Anti-aging analyses revealed that the STP endured for 108 h in a saline environment at 140 °C. In the water flooding characterization, the STP displayed a breakthrough pressure of 42.10 psi/ft. at a flow rate of 0.75 cm3/min. Under these extreme conditions, the plugging pressure reached 14.74 psi/ft., meeting the essential criteria for oilfield water plugging. This research demonstrates the potential of polysaccharides in the preparation of sustainable, tough, and heat-resistant water plugging materials.

How useful are YouTube videos of pacemaker implantation? An objective study to assess quality of information content

Abstract Background Permanent pacemakers (PPM) are a commonly performed, life-saving cardiac procedure. Patients often seek further information on medical interventions beyond traditional consultation spaces via the Internet, but such resources can contain varying amounts of procedure-critical information. This has not been previously assessed for PPM implantation. Objective To assess the level of patient-relevant information content in videos of PPM implantation on YouTube. Methods We performed searches on YouTube using the search terms "Pacemaker" and "PPM implantation". Both searches were performed twice for reproducibility. The first 100 results from each search were screened for inclusion. All English language videos covering transvenous pacemaker implantation were included. A list of key information criteria encompassing several domains (explanation of the procedure, indications, pre-operative considerations, operative details, post-operative care, risks of the procedure, aspects of daily life affected by PPM implantation, prognosis, and alternative treatment options) was generated from existing text resources, supplemented by expert opinion. Two authors (RDS, SR) independently assessed the videos for presence of the predefined information criteria. Results Of 196 unique results, 33 videos uploaded by 32 users met inclusion criteria (Figure 1). No single video contained all essential information criteria. The mean number of criteria covered in the videos was 8/32 (standard deviation 4.8), with a range of 0/32 to 17/32. Three criteria were not covered in any videos. Most videos discussed elements of the PPM implantation procedure, the components of a PPM, and the reasons for implantation. However, key aspects of pre-operative (need for pre-operative tests, medication management) and post-discharge (limiting arm movements on the side of implant, need to keep PPM identity card and contact details of department, driving restrictions, need for generator replacement and likely battery longevity) patient care were rarely discussed (Figure 2). There was also limited discussion of the potential risks of PPM implantation. Furthermore, three videos contained out-of-date information, giving explicit advice to avoid all magnetic resonance imaging. Conclusion Videos on YouTube on PPM implantation do not contain sufficient information to give patients sufficient overview of the procedure. In some cases, they contain out-of-date information that may adversely affect the decision to implant and deprive patients of important diagnostic tests. They lack key patient-centric information on the practicalities of care around the procedure, which is probably the information most relevant to and desired by patients. There is a need for a professionally regulated, exhaustive audio-visual resource for patients seeking further information on PPM implantation. Furthermore, there is a need for increased oversight of patient information material uploaded on the Internet.

Mapping the barrier and strategic solutions of halal supply chain implementation in small and medium enterprises

PurposeThis study aims to identify the challenges, promote respective solutions and construct strategies for the implementation of the halal supply chain in Indonesia’s small and medium-sized enterprises (SMEs).Design/methodology/approachThis research used the analytic network process in nine respondents categorised into three groups of relevant stakeholders: government, academia and industry.FindingsSeven essential criteria for the implementation of a halal supply chain in SMEs were identified, namely, the process, packaging, storage, transportation, fundamental aspects, supporting policy and technology. Notably, the high cost of adopting blockchain technology was the most crucial issue, particularly in SMEs.Practical implicationsThrough the findings, several critical factors to consider in the implementation of halal supply chains for SMEs were identified. The investment in halal supply chain technology, which incurs a high cost carried by entrepreneurs, is a burden for SMEs. For this reason, further studies are required to formulate and develop cost-effective halal supply chain technology for SMEs.Originality/valueTo the best of the authors’ knowledge, this research is the first attempt of comprehensively mapping the barriers and developing strategic solutions to implement the halal supply chain by Indonesia’s SMEs.

Diagnostic Biomarkers in Renal Cell Tumors According to the Latest WHO Classification: A Focus on Selected New Entities.

The fifth edition of the World Health Organization (WHO) classification for urogenital tumors, released in 2022, introduces some novelties in the chapter on renal epithelial tumors compared to the previous 2016 classification. Significant changes include the recognition of new disease entities and adjustments in the nomenclature for certain pathologies. Notably, each tumor entity now includes minimum essential and desirable criteria for reliable diagnosis. This classification highlights the importance of biological and molecular characterization alongside traditional cytological and architectural features. In this view, immunophenotyping through immunohistochemistry (IHC) plays a crucial role in bridging morphology and genetics. This article aims to present and discuss the role of key immunohistochemical markers that support the diagnosis of new entities recognized in the WHO classification, focusing on critical topics associated with single markers, in the context of specific tumors, such as the clear cell capillary renal cell tumor (CCPRCT), eosinophilic solid and cystic renal cell carcinoma (ESC-RCC), and so-called "other oncocytic tumors", namely the eosinophilic vacuolated tumor (EVT) and low-grade oncocytic tumor (LOT). Their distinctive characteristics and immunophenotypic profiles, along with insights regarding diagnostic challenges and the differential diagnosis of these tumors, are provided. This state-of-the-art review offers valuable insights in biomarkers associated with novel renal tumors, as well as a tool to implement diagnostic strategies in routine practice.

Advances in Two-Dimensional Ion-Selective Membranes: Bridging Nanoscale Insights to Industrial-Scale Salinity Gradient Energy Harvesting.

Salinity gradient energy, often referred to as the Gibbs free energy difference between saltwater and freshwater, is recognized as "blue energy" due to its inherent cleanliness, renewability, and continuous availability. Reverse electrodialysis (RED), relying on ion-selective membranes, stands as one of the most prevalent and promising methods for harnessing salinity gradient energy to generate electricity. Nevertheless, conventional RED membranes face challenges such as insufficient ion selectivity and transport rates and the difficulty of achieving the minimum commercial energy density threshold of 5 W/m2. In contrast, two-dimensional nanostructured materials, featuring nanoscale channels and abundant functional groups, offer a breakthrough by facilitating rapid ion transport and heightened selectivity. This comprehensive review delves into the mechanisms of osmotic power generation within a single nanopore and nanochannel, exploring optimal nanopore dimensions and nanochannel lengths. We subsequently examine the current landscape of power generation using two-dimensional nanostructured materials in laboratory-scale settings across various test areas. Furthermore, we address the notable decline in power density observed as test areas expand and propose essential criteria for the industrialization of two-dimensional ion-selective membranes. The review concludes with a forward-looking perspective, outlining future research directions, including scalable membrane fabrication, enhanced environmental adaptability, and integration into multiple industries. This review aims to bridge the gap between previous laboratory-scale investigations of two-dimensional ion-selective membranes in salinity gradient energy conversion and their potential large-scale industrial applications.

Identification of novel hit molecules targeting M. tuberculosis polyketide synthase 13 by combining generative AI and physics-based methods

In this work we investigated the Pks13-TE domain, which plays a critical role in the viability of the mycobacteria. In this report, we have used a series of AI and Physics-based tools to identify Pks13-TE inhibitors. The Reinvent 4, pKCSM, KDeep, and SwissADME are AI-ML-based tools. AutoDock Vina, PLANTS, MDS, and MM-GBSA are physics-based methods. A combination of these methods yields powerful support in the drug discovery cycle. Known inhibitors of Pks13-TE were collected, curated, and used as input for the AI-based tools, and Mol2Mol molecular optimisation methods generated novel inhibitors. These ligands were filtered based on physics-based methods like molecular docking and molecular dynamics using multiple tools for consensus generation. Rigorous analysis was performed on the selected compounds to reduce the chemical space while retaining the most promising compounds. The molecule interactions, stability of the protein-ligand complexes and the comparable binding energies with the native ligand were essential factors for narrowing the ligands set. The filtered ligands from docking, MDS, and binding energy colocations were further tested for their ADMET properties since they are among the essential criteria for this series of molecules. It was found that ligands Mt1 to Mt6 have excellent predicted pharmacokinetic, pharmacodynamic and toxicity profiles and good synthesisability.

Dimensional Analysis based Prediction Model for Fuel Consumption in the Deutz Agrotrac Tractor

Background: Fuel consumption is a critical factor in the performance of an agricultural tractor. And it can be affected by numerous parameters. Farming practices is an essential aspect that affects the cost of operation and the overall efficiency of the tractor. Predictions of fuel consumption rates in tractors and the energy consumption parameters of primary tillage equipment under local conditions are therefore essential selection criteria in purchasing decisions. Methods: A prediction model for fuel usage during tillage operations was created using dimensional analysis. The model was established by incorporating experimental findings into an equation. The experiment was conducted in the El Ouracia region of Setif, Algeria in 2022/2023 crop season, with fuel usage per time unit determined through topping-up the tank method. The fuel experiment parameters were measured according to their respective standard procedures. Result: By simulating fuel usage with tillage depth, tillage width, travel speed, soil bulk density and cone index. The constant in the prediction model was obtained. This developed model has the potential to forecast the tractor fuel consumption during tillage operation.