Relevant Relationships Research Articles

The use and application of Lean Management methods to research processes—a scoping review protocol

IntroductionWaste in medical research is a relatively well-known issue. However, only a few initiatives exist to address this issue. Lean Management methods (Lean) were developed in industrial manufacturing and later...

Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation.

Adaptive stress response pathways (SRPs) restore cellular homeostasis following perturbation but may activate terminal outcomes like apoptosis, autophagy, or cellular senescence if disruption exceeds critical thresholds. Because SRPs hold the key to vital cellular tipping points, they are targeted for therapeutic interventions and assessed as biomarkers of toxicity. Hence, we are developing a public database of chemicals that perturb SRPs to enable new data-driven tools to improve public health. Here, we report on the automated text-mining pipeline we used to build and curate the first version of this database. We started with 100 reference SRP chemicals gathered from published biomarker studies to bootstrap the database. Second, we used information retrieval to find co-occurrences of reference chemicals with SRP terms in PubMed abstracts and determined pairwise mutual information thresholds to filter biologically relevant relationships. Third, we applied these thresholds to find 1206 putative SRP perturbagens within thousands of substances in the Library of Integrated Network-Based Cellular Signatures (LINCS). To assign SRP activity to LINCS chemicals, domain experts had to manually review at least three publications for each of 1206 chemicals out of 181,805 total abstracts. To accomplish this efficiently, we implemented a machine learning approach to predict SRP classifications from texts to prioritize abstracts. In 5-fold cross-validation testing with a corpus derived from the 100 reference chemicals, artificial neural networks performed the best (F1-macro = 0.678) and prioritized 2479/181,805 abstracts for expert review, which resulted in 457 chemicals annotated with SRP activities. An independent analysis of enriched mechanisms of action and chemical use class supported the text-mined chemical associations (p < 0.05): heat shock inducers were linked with HSP90 and DNA damage inducers to topoisomerase inhibition. This database will enable novel applications of LINCS data to evaluate SRP activities and to further develop tools for biomedical information extraction from the literature.

POLICY RECOMMENDATION FOR INTEGRATED SMART HEATING SYSTEM

In the context of the challenges posed by global climate change and the need for a sustainable energy transition, this study addresses the ways in which innovative strategies contribute to the formulation of public policies aimed at optimising heating systems. This research aims to identify solutions to reduce greenhouse gas emissions and to increase energy efficiency in the field of heating, essential aspects in achieving global sustainability goals to formulate policy recommendations for an integrated heating system. Adopting a mixed methodological approach, this analysis combines the literature review with a systematic examination of different initiatives and solutions adopted at the urban level to extract patterns of good practice and highlight relevant relationships and differences. The research emphasises the importance of the synergy between innovation, governance, and financing mechanisms in promoting sustainable and effective solutions. In the light of good practices and lessons learned from cities such as Copenhagen, Stockholm, Helsinki, Vancouver, and Freiburg, the authors' contribution focuses on identifying governance strategies that facilitate the transition to optimised heating systems. These cities demonstrate how the implementation of well-designed public policies can act as a catalyst for the adoption of sustainable heating solutions, highlighting the essential role of public policy in mediating urban development needs and the effective implementation of sustainability initiatives. The research results show that adopting an integrated and participatory approach involving all relevant actors can speed up the adoption of more efficient heating systems with reduced environmental impact. This underlines the importance of adopting legislative and public policy frameworks that stimulate heating innovation and encourage collaboration between the public, private and community sectors. Beneficiaries of this research include policy makers, energy professionals, and the academic community, providing them with a solid foundation for the development and implementation of effective public policies. The study concludes that it is essential to develop public policy strategies that promote the adoption of sustainable heating solutions, based on lessons learned from cities that have successfully implemented such initiatives. Thus, progress towards a sustainable energy future can be accelerated, contributing significantly to global efforts to reduce the negative impact on the environment.

Africa's natural fibres used in polymer composites: A systematic review

AbstractEnvironmental concerns and the depletion of petroleum resources have spurred research into natural fibres as sustainable alternatives to synthetic fibres as the reinforcement phase in polymer composites. Given that the local availability of materials is a crucial component in the sustainability framework, there is a need to map out the fibres used to develop natural fibre composites across geographical regions to optimize local resource utilization. Through a systematic review of publications sourced from Scopus and Web of Science databases, this study examines the contributions made by Africa to develop green polymer composites. The bibliometric data from both databases were systematically merged, and bibliometric analysis was carried out to identify trends and relevant relationships and provide a more general insight into Africa's progress in the natural fibre polymer composite field. A meta‐analysis was then conducted to identify the natural fibres exclusively sourced from Africa that have been used to develop polymer composites. The study also discussed natural fibre classifications with respect to fibre type and form. Sisal, palm varieties (particularly date palm), alfa, jute and members of the Musaceae family (i.e., banana, plantain and enset) were found to be the most used African‐sourced fibres. This study is a step to creating a more extensive global natural fibre database that seeks to provide more precise knowledge, enhance research efficiency, and ensure the utilization of local materials in creating more sustainable composites.Highlights The use of local materials is a key component of sustainable development A natural fibre database can foster sustainability in the composite industry Egypt, Morocco, and Tunisia are leading Africa's composite research Research prioritizes composite material science over practical applications Sisal, date palm, alfa and jute are the most used natural fibres in Africa

Targeted genetic analysis in a cohort of sporadic death from spontaneous rupture of thoracic aortic dissection in Han Chinese population

PurposeThoracic aortic dissection (TAD) is a life-threatening cardiovascular disease that often results in sudden cardiac death (SCD). However, the genetic characteristics of individuals with TAD confirmed at autopsy have been rarely studied. Our objective was to determine the prevalence of pathogenic variants in TAD-associated genes in a cohort of sporadic deaths resulting from spontaneous rupture of TAD and identify relevant genotype-phenotype relationships in Han Chinese population. MethodsWe included sixty-one consecutive sporadic decedents whose primary cause of death was spontaneous rupture of TAD, and performed a whole exome sequencing based strategy comprising 26 known TAD-associated genes. ResultsWe identified 7 pathogenic or likely pathogenic (P/LP) variants in 7 cases (11.48 %) and 22 variants of uncertain significance (VUS) in 22 cases (36.07 %). The FBN1 gene was found to be the major disease-causing gene. Notably, TAD decedents with P/LP variant exhibited significantly earlier mortality. Moreover, we reported for the first time that TAD decedents with P/LP variant had a shorter diagnosis and treatment time. ConclusionOur study investigated the genetic characteristics of TAD individuals confirmed until autopsy in Han Chinese population. The findings enhanced the understanding of the genetic underpinnings of TAD and have significant implications for clinical management and forensic investigations.

Evolution of volatile compounds of baked dried tofu during catalytic infrared baking process and their correlation with relevant physicochemical properties.

Energy-saving and low-carbon baking processes, as well as the need to determine the flavor-forming mechanisms of baked dried tofu, are becoming increasingly necessary. The application of emerging catalytic infrared radiation (CIR) technology in baking of dried tofu is considered of high interest due to the low energy consumption and high baking efficiency compared to traditional baking methods. Hence, this study aimed to investigate the evolution of aroma compounds in baked dried tofu during the CIR baking process and reveal relevant relationships between physical qualities, potential flavor precursors and key volatile compounds. The results showed that the surface color of dried tofu gradually turned an appetizing golden yellow color during the rapid heating process, caused by the uniform infrared radiation from the radiant emitters. Meanwhile, the moisture of dried tofu experienced minimal reduction and the hardness of dried tofu gradually increased with the formation of crust on the surface. In addition, 49 volatile compounds were identified by headspace solid-phase microextraction-gas chromatography-mass spectrometry and 13 substances - 1-hexanol, 1-octen-3-ol, 1-pentanol, heptanal, nonanal, hexanal, (E,E)-2,4-decadienal, (E,Z)-2,4-decadienal, octanal, (E)-2-octenal, (E)-2-nonenal, 2-heptanone and 2-pentylfuran - were confirmed as key aroma compounds. Moreover, the amino acids aspartic acid, glutamic acid, isoleucine, lysine and arginine, and the fatty acids butyric, caprylic, capric, tridecanoic, stearic, oleic and linolenic were responsible for the unique flavor of CIR-baked dried tofu. Consequently, the findings can provide a scientific basis for manufacturers to achieve precise quality control and large-scale production of CIR-baked dried tofu products. © 2024 Society of Chemical Industry.

The influence of a previous implant-based breast reconstruction on postoperative sensation of the deep inferior epigastric artery perforator flap

BackgroundImplants and DIEP flaps have different outcomes regarding postoperative breast sensation. When compared to the preoperative healthy breast, implant-based breast reconstruction (IBBR) negatively influences postoperative breast sensation. However, it is currently unknown whether a prior IBBR also influences postoperative sensation of a replacing DIEP flap. The goal of this cohort study is to evaluate the influence of an IBBR on the postoperative sensation of a replacing DIEP flap.MethodsWomen were included if they received a DIEP flap reconstruction after mastectomy, with or without prior tissue expander (TE) and/or definitive breast implant. Sensation was measured at four intervals in 9 areas of the breast with Semmes–Weinstein monofilaments: T0 (preoperative, implant/no reconstruction), T1 (2–7 months postoperative, DIEP), T2 (± 12 months postoperative, DIEP), Tmax (maximum follow-up, DIEP). Linear mixed-effects models were used to investigate the relationship between an implant/TE prior to the DIEP flap and recovery of breast sensation.Results142 women comprising 206 breasts were included. 48 (23.3%) breasts did, and 158 (76.7%) breasts did not have a TE/IBBR prior to their DIEP. No statistically significant or clinically relevant relationships were found between a prior implant/TE and recovery of DIEP flap breast sensation for the flap skin, native skin, or total breast skin at T1, T2, or Tmax. There were also no relationships found after adjustment for the confounders radiation therapy, BMI, diabetes, age, flap weight, follow-up, and nerve coaptation.ConclusionsAn implant/TE prior to a DIEP flap does not influence the recovery of postoperative breast sensation of the DIEP flap.

Metastases and Primary Brain Tumors Affecting the Fornix of the Brain.

Background The aim of this study is to evaluate the clinical and radiological findings of metastatic tumors and primary brain tumors affecting the fornix. Methods Between January 2015 and March 2023, we retrospectively evaluated 1087 patients of both sexes who underwent cranial magnetic resonance imaging (MRI) for a preliminary diagnosis of intracranial malignancy in the radiology department of our hospital. Two radiologists with six and 10 years of experience in MRI examination assessed the relationship between primary and metastatic tumors and the fornix. Results Involvement of the fornix was diagnosed in 29 of the 1087 patients (2.66%), of which fornix was affected by metastatic lesions in 14 patients (48.2%) and primary tumors in 15 patients (51.7%).The majority of metastatic lesions were from lung and breast cancers, with other tumor types including osteosarcoma, renal cell carcinoma, pancreatic adenocarcinoma, pleomorphic sarcoma, and diffuse large B-cell lymphoma. Among all primary tumors, glioblastoma was the most common primary brain tumor invading the fornix, with other diagnoses including diffuse astrocytoma, medulloblastoma, and anaplastic oligodendroglioma.Metastatic and primary brain tumors affecting the fornix were detected over a broad timeline, from the time of diagnosis up to 120 months after diagnosis. A retrospective evaluation of medical records revealed memory deficits in four patients. Conclusion The fornix can be affected by both metastatic and primary brain tumors. It is crucial to understand the relevant neuroanatomical relationships when evaluating lesions that affect the fornix.

Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains

AbstractIn this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

Metal−support interaction in single-atom electrocatalysts: A perspective of metal oxide supports

The discovery of single-atom catalysts (SACs) represents a groundbreaking advancement in the field of catalysis over the past decades. With the in-depth exploration of relevant structure-activity relationships, the metal-support interaction (MSI) is widely adopted to elucidate variations in electronic structure and coordination configuration of atomic active sites on various kinds of supports. Herein, we briefly summarize the metal oxide supports for SACs fabrication, including the distinctive characteristics of metal oxide supports, enlightening advancements in metal oxide support-based SACs (MO-SACs), feasible preparation methods for MO-SACs and effective regulation strategies of MSI effect in MO-SACs. In addition, we present our viewpoints and outlook in this field to stimulate rational design and construction of novel MO-SACs applied in diverse renewable energy devices, while some universal suggestions are sincerely given to provoke thoughtful considerations during the research process.

An analysis of fog and low stratus life‐cycle regimes over central Europe

AbstractA better understanding of fog and low stratus (FLS) life cycles, in particular the typical onset and dissipation times, can help traffic safety and solar power planning. Besides its high dependence on the prevalent meteorological conditions, the FLS life cycle is further determined by the FLS type as well as the underlying geography and climate. While satellite‐based FLS data sets with high temporal and spatial resolution are available, an objective, large‐scale, satellite‐based classification of FLS life‐cycle regions, which would allow for more targeted analyses of the FLS life cycle, is lacking. In this study, a hierarchical clustering algorithm is applied to identify regions of similar relationships of the FLS life cycle to environmental conditions over central Europe. The clustering reveals major FLS life‐cycle regimes with distinct differences in FLS occurrence, temporal FLS life‐cycle patterns, and climatic characteristics. Based on regime‐specific sensitivity analyses, the relationships of the FLS life cycle with near‐ground temperature and specific humidity are identified as the most relevant input relationships for the clustering algorithm, especially in the Mediterranean region. FLS life‐cycle regimes are further presented at a regional scale, outlining the applicability of the derived FLS life‐cycle regimes to future regional process‐oriented FLS life‐cycle studies.

Information Placement in Notarial Registries: Issues with Evaluating the Actions of Participants

Within the framework of improving legislation, the Federal Notary Chamber has been entrusted with the responsibility of maintaining a registry of notifications regarding the pledge of movable property and the cancellation of powers of attorney executed in simple written form. It should be noted that these changes have a positive impact on civil transactions. However, there are specific questions regarding the procedure for their implementation. The main issue is that neither the notary nor the person posting the relevant information about the pledge or cancellation of powers of attorney is held responsible for the accuracy of the information, which allows for the possibility of abuse. In defining the purpose of this research, attention should be paid to the evaluation and analysis of the procedural and legal aspects of maintaining the aforementioned registries, identifying specific cases of abuse of rights by individuals posting information in the respective registries. This necessitates finding a solution to the stated problem, namely: clarifying the procedure and limits of actions for the parties involved in the relevant legal relationships in order to prevent the possibility of their misconduct. The research is based on general scientific methods of cognition and legal hermeneutics. During the analysis of current legislation and legal practices, it has been determined that in the existing reality, there is a possibility of abuse by individuals posting information in notarial registries regarding the cancellation of powers of attorney and the registry of notifications about pledges. The legislation does not provide indications of sanctions against individuals who violate the prescribed registry procedure. The presumption of notification from the moment the information is posted in the registry by an interested party, despite possible errors that compromise the accuracy of electronic search or distortions in the information, which prevent proper identification of the sought-after object, leads to violations of property rights of participants in civil transactions.

Potentially meaningful teaching unit with the transversal theme traffic education for the teaching of kinematics in Sciences

This paper presents the results of a Potentially Significant Teaching Unit (PSU), with the cross-cutting theme "Traffic Education", applied to a ninth grade class. This work derives from a qualitative study whose aim was to verify the potential of a PSU to promote meaningful learning of kinematics content. The materials and stages of the UEPS were based on the Meaningful Learning Theory. The assessment carried out during the UEPS was formative in nature, as the students were monitored as they carried out the tasks in the different stages. The data from the various assessment instruments was analyzed using descriptive statistics and Textual Discourse Analysis. The analysis showed that the aim of this work was achieved, as there was progress in understanding kinematics concepts and it helped to improve the students' attitudes to deal more adequately with the complexity of the "Traffic" phenomenon. The study showed that the use of this cross-cutting theme produced relevant relationships for learning, contributing to new ways of teaching and learning science. This proposal therefore constitutes material that can be qualified as having the potential to develop meaningful learning.

The formalism of governance on the performance of family SMEs in chad

The aim of this study is to analyze the effects of family SME governance on their performance. Thus, the concern of this work is to present the most relevant agency relationships for analyzing the governance of family SMEs and the family factors that can be analyzed from the theoretical framework of agency and stewardship, given the limitations of agency theory for the study of family SME governance. The study is based on a sample of 182 Chadian family SMEs from a variety of sectors. The investigation is based on a hypothetico-deductive method, and the research results show that the impact of governance on performance is significant. A Principal Component Analysis (PCA) was carried out to identify specific factors for the three groups of variables: governance, altruism and family traits. Factor regression by respective degree of significance and importance of the factors shows that the factors governance formalism, relationships and delegations, internal relationships, training and experience and professional conflicts are the main drivers of SME performance. Finally, the impact of the altruism variable on performance is insignificant. In conclusion, the theoretical and managerial implications are discussed, along with the main avenues for future research.

Human Understanding and Perception of Unanticipated Robot Action in the Context of Physical Interaction

Anticipating a future scenario where the robot initiates its own actions and behaves voluntarily when collaborating with humans, our research focuses on human understanding and perception of unanticipated robot actions during physical human-robot interaction. While the current literature searches for key factors that make the human-robot collaboration successful, the question of how people experience the robot’s unanticipated action as cooperative or uncooperative seems to remain open. We designed a game-based experiment (N = 35) where the participant played a “catch-falling-coins” game by moving a robotic arm. Our experiment introduced unanticipated robot actions in an “active session” where the robot targeted higher-valued coins without first informing the participants. Through semi-structured interviews and statistical analysis of questionnaires (Big Five Personality Test, SAM, NARS and CH33), we examined the participants’ understanding of the robot’s “intention” and their positive or negative perception of the robot as cooperative or uncooperative. Among the participants who understood that the robot’s “intention” was to catch the higher-valued coins, the majority of them reported a positive perception of the robot (cooperative or helpful) while this was not the case among those who did not understand the robot’s intention. We also observed relevant relationships between some personality traits and a person’s understanding of the robot’s intention. Qualitative analysis of the interviews allowed us to structure the process of perception change during the game into three phases: confusion, investigation, and adaptation. We believe that our research contributes to the study of human perception, and particularly to the relationship between a human’s understanding of unanticipated robot actions and their positive or negative perception of the robot.

GC-CDSS: Personalized gastric cancer treatment recommendations system based on knowledge graph

BackgroundGastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and screening is increasing rapidly. ObjectiveThe purpose of this study is to (1) summarize the treatment decision process for GC according to the treatment guidelines in China, and then create a knowledge graph (KG) for GC, (2) based on aforementioned KG, built a CDSS and conducted an initial feasibility evaluation for the current system. MethodsFirstly, we summarized the decision-making process for treatment of GC. Then, we extracted relevant decision nodes and relationships and utilized Neo4j to create the KG. After obtaining the initial node features for building the graph embedding model, graph embedding algorithm, such as Node2Vec and GraphSAGE, were used to construct the GC-CDSS. At last, a retrospective cohort study was used to compare the consistency between GC-CDSS and MDT in treatment decision making. ResultsIn current study, we introduce a GC-CDSS, which is constructed based on Chinese GC treatment guidelines knowledge graph (KG). In the KG, we define four types of nodes and four types of relationships, and it comprise a total of 207 nodes and 300 relationships. Regarding GC-CDSS, the system is capable of providing dynamic and personalized diagnostic and treatment recommendations based on the patient's condition. Furthermore, a retrospective cohort study is conducted to compare GC-CDSS recommendations with those of the MDT group, the overall consistency rate of treatment recommendations between the auxiliary decision system and MDT team is 92.96%. ConclusionsWe construct a GC treatment support system, GC-CDSS, based on KG. The GC-CDSS may help oncologists make treatment decisions more efficient and promote standardization in primary healthcare settings.

Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis

PurposeEpistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom fully explored as most approaches primarily focus on single-locus effects, partly because analyzing all pairwise and higher-order interactions requires significant computational resources. Furthermore, existing methods for epistasis detection only consider a Cartesian (multiplicative) model for interaction terms. This is likely limiting as epistatic interactions can evolve to produce varied relationships between genetic loci, some complex and not linearly separable.MethodsWe present new algorithms for the interaction coefficients for standard regression models for epistasis that permit many varied models for the interaction terms for loci and efficient memory usage. The algorithms are given for two-way and three-way epistasis and may be generalized to higher order epistasis. Statistical tests for the interaction coefficients are also provided. We also present an efficient matrix based algorithm for permutation testing for two-way epistasis. We offer a proof and experimental evidence that methods that look for epistasis only at loci that have main effects may not be justified. Given the computational efficiency of the algorithm, we applied the method to a rat data set and mouse data set, with at least 10,000 loci and 1,000 samples each, using the standard Cartesian model and the XOR model to explore body mass index.ResultsThis study reveals that although many of the loci found to exhibit significant statistical epistasis overlap between models in rats, the pairs are mostly distinct. Further, the XOR model found greater evidence for statistical epistasis in many more pairs of loci in both data sets with almost all significant epistasis in mice identified using XOR. In the rat data set, loci involved in epistasis under the XOR model are enriched for biologically relevant pathways.ConclusionOur results in both species show that many biologically relevant epistatic relationships would have been undetected if only one interaction model was applied, providing evidence that varied interaction models should be implemented to explore epistatic interactions that occur in living systems.

Spirituality and volunteering in soft skills development

This paper analyses the main relationships between the perception of spirituality, participation in volunteer projects and the development of soft skills. 309 questionnaire forms were applied and the method of multivariate analysis of linear regression was used. Relevant relationships were found between the constructs. The variable related to learning proved to be decisive for the decision to participate in volunteer projects, demonstrating the interest of volunteers in this type of development. In addition, the higher level of personal spirituality, according to the respondent's perception, favours the development of soft skills, in addition to active participation in volunteering, not occasional, but frequent and systematic, preferably weekly. On the one hand, the company can stimulate spirituality passively or actively. On the other hand, the company can allow, encourage and even promote weekly participation in volunteer projects. Faced with the need for organizations to develop Soft Skills, this work contributes to the proposal of alternative ways to increase these skills, in view of the perception that courses and business schools have not achieved this objective. Results can also contribute to society by demonstrating that the effort to meet the needs of others can bring individual benefits to those who dedicate themselves to this task.

A Physical Model-Based Approach to One-Point Calibration of Pulse Transit Time to Blood Pressure.

To develop a novel physical model-based approach to enable 1-point calibration of pulse transit time (PTT) to blood pressure (BP). The proposed PTT-BP calibration model is derived by combining the Bramwell-Hill equation and a phenomenological model of the arterial compliance (AC) curve. By imposing a physiologically plausible constraint on the skewness of AC at positive and negative transmural pressures, the number of tunable parameters in the PTT-BP calibration model reduces to 1. Hence, as opposed to most existing PTT-BP calibration models requiring multiple (≥2) PTT-BP measurements to personalize, the PTT-BP calibration model can be personalized to an individual subject using a single PTT-BP measurement pair. Equipped with the physically relevant PTT-AC and AC-BP relationships, the proposed approach may serve as a universal means to calibrate PTT to BP over a wide BP range. The validity and proof-of-concept of the proposed approach were evaluated using PTT and BP measurements collected from 22 healthy young volunteers undergoing large BP changes. The proposed approach modestly yet significantly outperformed an empiric linear PTT-BP calibration with a group-average slope and subject-specific intercept in terms of bias (5.5 mmHg vs 6.4 mmHg), precision (8.4 mmHg vs 9.4 mmHg), mean absolute error (7.8 mmHg vs 8.8 mmHg), and root-mean-squared error (8.7 mmHg vs 10.3 mmHg, all in the case of diastolic BP). We demonstrated the preliminary proof-of-concept of an innovative physical model-based approach to one-point PTT-BP calibration. The proposed physical model-based approach has the potential to enable more accurate and convenient calibration of PTT to BP.

Avoiding food waste from restaurant tickets: a big data management tool

PurposeThis study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand.Design/methodology/approachA system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers.FindingsThe study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior.Research limitations/implicationsThis study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications.Originality/valueThe value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.