Price, Cost and Income (PCI) are distinct economic indicators intrinsically linked to the values they denote. These observables take center stage in the multi-criteria decision-making process that enables economic agents to convey subjective utilities of market-exchanged commodities objectively. The valuation of these commodities heavily relies on PCI-based empirical observables and their supported methodologies. This valuation measure’s accuracy is critical, as it influences subsequent decisions within the market chain. However, measurement errors often arise due to inherent uncertainties in the value state, impacting economic agents’ wealth, particularly when trading significant commodities such as real estate properties. This paper addresses this issue by incorporating entropy measurements into real estate valuation. This mathematical technique adjusts and integrates triadic PCI estimates, improving the final stage of appraisal systems where definitive value decisions are crucial. Employing entropy within the appraisal system can also aid market agents in devising informed production/trading strategies for optimal returns. The results from our practical demonstration indicate promising implications. The entropy’s integration with PCI estimates significantly improved the value measurement’s precision and reduced economic decision-making errors. The heart of economics, and more specifically, appraisal practice, primarily revolves around interpreting and quantifying the market value of real assets ,2,3. In Indeed, market value estimation for a given property, herein referred to as the “subject”, can be achieved using the three fundamental methods of price, cost and income, each involving detailed computation steps . ConsideIn the last step of the evaluation process, working with the results of the EWM, we remarked that it has the potential to improve the current system of evaluation in a global manner as well as in a case-by-case basis. In addition to this global approach that estimates a fused value for all the responses in the whole data, we also tried the EWM in case-by-case evaluations, adjusting each imperfect estimation of conventional approaches. In that perspective, we improved and adjusted the EWM in several regards, for instance, by integrating the Kullback-Leibler divergence in relative entropies of each case in the data. This is another important contribution of our work as it not only allows a value estimate for each of the triadic estimates in the data, but it also provides a validation basis with all estimates showing a trend in their behavior that logically should converge to a constant value .In this work, we exemplify how the EWM approach effectively addresses the limitations of triadic methods, merging them into dependable point estimates. This technique streamlines and completes the computational cycle within the conventional appraisal system, enhancing the transparency, elegance and depth of the appraisal system when pinpointing value based on the simultaneous utilization of triadic methodologies. By surmounting the limits inspiring this work, we can more fully appreciate the process of pinpointing a singular value from the simultaneous use of three distinct market responses. From a conceptual perspective, acknowledging three different market values that often diverge significantly for the same property offers the analytical capability to compare, justify and explain results, rather than relying on a single method. This approach potentially equalizes the analytical and repetitive technical content in appraisal reports, much of which becomes automated with advanced technology and data, leaving less room for expert insight and knowledge. The progressive automation of appraisal steps trims costs, streamlines report format and content, and exerts pressure on the profession to cultivate more sophisticated and analytical content. This unique analytical opportunity, confined to the final step of the appraisal process, can stimulate intriguing advancements.Reliable estimates of value are essential for a wide range of agents, including property owners, investors, cities, governments, developers, constructors, buyers, sellers and institutions that lend capital. In addition to being important for experts and these agents, proper decisions regarding real estate value are also necessary for managers at various levels and types of properties ,25. In aEconomic agents evaluate various events or objects of desire based on their degree of expectations and information. Theories of judgment and information help to understand their subjective behaviors in forming these evaluations ,30. InfoEntropy calculations can be used in engineering , populatIn economic behavior, the reduction of entropy is clearly a key concept. According to Schrödinger , a NobelThough the literature provides formal definitions of thermodynamic and informational entropies (see the comprehensive work by ), drawinIn the context of economic valuation, decisions regarding desired events/objects are often made in uncertain environments. To make these decisions, information or different types of observables such as PCI are used to feed personal or expert evaluation methods . HoweverTo integrate attribute contributions or estimates from multiple methods into one indication for decision making, it is necessary to rank and weight them appropriately. Various methods have been developed for this purpose, including the eigenvalue method, which captures rank orders , conjoinEntropy calculations are known to be versatile and compatible methods, particularly in assigning priority and importance ratings of attributes/methods ,90. EntrSeveral studies have explored and integrated the potential of the entropy method in various ways and goals in real estate analyses . Zhou etValue holds profound significance and application in nearly all fields, with particular emphasis in economics ,115. HowTo elucidate the basis of value, authors traditionally differentiate between use value and exchange value ,123. ClaThe perspective of exchange value interprets the value of commodities by their observed PCI in the market ,128. In PCI involves a comparative process of negotiation and multi-criteria decision making, taking into account property attributes in relation to their impact on the market. Supply and demand agents negotiate and decide on selling price levels, cost of production entrepreneurs and income stream investors, all referring to the position of value as different bases of information. For instance, the price is an observed (or past) expression of value state resulting from an evaluative and comparative decision-making process by subjective buyers and sellers. The price does not equate to a value state; it serves as its imperfect reference . The same decisional process between two different types of economic agents, observed for different manners and in two additional different contexts, leads to two other observables of cost  and income (related to the same commodity in postponement/projections and strategic planning of future streams of periodic incomes).Consider the negotiation contexts for a residential property, as depicted in The final negotiated price provides one dimension of the property’s value state, but there are also the cost and income dimensions that, when taken together, give a more comprehensive perspective on the most probable position of the market value of the property . ImportaThe process of adjusting, either upward or downward, in the appraisal system is crucial to ensuring that the attributes and PCI estimates of comparable properties align closely with those of the subject property. What’s important to note about this adjustment process is that all necessary modifications have been implemented to make the property comparable; hence, any potential variations have been accounted for. At this final stage of the evaluation process, the expert also has to make a final decision on the most probable market value of the same property, which serves as the best approximation of the value state. Each valuation method carries its own advantages, disadvantages and unique characteristics, which depend on various factors. These include the type of property (certain methods are more suitable for specific property types), the availability of data, the extent of required computations/adjustments and the current state of the market.Sales comparison approach (SCA), the Cost summation approach (CSA) and the Income capitalization approach (ICA). The SCA is a more direct way of estimating the market price of a property, as it relies on the observed prices of comparable properties in the market. When the data from the market is poor regarding price and income, the cost method remains an alternative for the market value estimation of generally unusual properties. On the other hand, the CSA cannot estimate land value and may be influenced by cost depreciation estimation. The ICA is preferred for properties that generate stable income and have reliable market indicators like a stabilized cost and income, but it relies on projected and hypothetical data that are uncertain and derived from other estimations [The appraisal process can use three concurrent methods, each supported by PCI observables, respectively: the imations ,132.It is generally assumed that the application of the three methods simultaneously would result in three identical or closely similar values for the same property. In the example we use below as a practical demonstration, the SCA, CSA and ICA provided estimates of $362,000; $341,000 and $358,000, respectively. The expert must then decide on the final market value of the property based on local data at a specific date. The expert may suggest the SCA estimate of $362,000 because the data is recent and abundant on this market, in comparison to the results of the two other methods. An average of $354,000 is another alternative of value response of the subject, and a weighted average based on the reliability of each method would indicate a value of $357,000, assuming weights of 0.6, 0.2 and 0.2 by the expert’s intuition and knowledge of the market. These are the two known alternatives to conventional PCI evaluations . PractitIn the considered example, the variances between the estimation methods may vary depending on the subject of inquiry. In these instances, all the potential of data, parameters, computations and approaches have been involved in order to bring all the necessary adjustments. The same subject is evaluated by the same method with low internal variance, yet the values between methods often do not converge. It is challenging to logically explain and improve prediction processes and approaches in such situations, even when using competitive triadic approaches and following a thorough evaluation process. This poses a major concern for experts and decision makers because the most critical step in the evaluation process, the decision-making moment, becomes void. Consequently, PCI expressions by economic agents and the considerations that lead to market values by experts cannot be confidently used in MCDM. Even if estimates converge, the value state largely retains inefficiencies using the current framework of classic evaluation.The Entropy weights method (EWM) works well across diverse MOO problems in MCDM . ShannonTo compute uncertain information (Entropy), probability theory is utilized. The EWM works on the principle that superior weight indicator information is more constructive than the lower indicator information . This meIn this research, we propose that value has a basis that can be explored and approached in the entropy framework. We present the basis of this approach in the following sections with equations of the EWM. Numerous alternative techniques can be specified to integrate and improve the real estate evaluation process within the general framework of the EWM. It’s important to note that our approach picks up where traditional PCI evaluation methods leave off, offering a singular market value. This market value is an approximation derived from averaging three different market values, which are based on SCA, CSA and ICA. While this averaging process provides a valuable perspective on a property’s market value, there still exist variances between triadic approaches. To mitigate these variances, we strive to introduce an objective weighting using the EWM. Our weighting process begins by utilizing three PCI market values, under the assumption that all the necessary adjustments have already been made in their detailed computations. The market value produced by the EWM is expected to be more objective and efficient, provided its results converge to a singular value state over a set number of trials . We will delve deeper into this in the following section, but first, we will present our approach as follows:The decision matrix of data is detailed in Equation (1) in which every row of decision is allotted to one experiment and all columns to one determining variable . Accordingly, the elements The linear normalization technique is utilized to make the experimental data of DM dimensionless due to several units of the variables. Equation (2) is used for beneficial attributes, i.e., those having positive impacts between them and value.The above equation assumes that evaluation response variables are in positive relation between them and value. In case a variable among them negatively affects the value state, then the Equation (2) becomes The probability of each variable The following Equation (4) is utilized to calculate the Entropy Note that The ratio between In this equation, It must be remembered that the effect of the logarithm in the entropy formula is to transform multiplication into addition and division as indicated in the Equation (7).When non-additive entropies are involved, as we assume to be the case in this work, there is a certain dependence between explicative/determining variables. It is imperative to identify these non-additive mutual entropies and measure them . We did The mutual information defined by the Equation (8) represents the degree of divergence from the linearity of the entropies. This equation applies in the case of attributes with positive impacts on value. When the impact is negative between attributes, it becomes The larger the From the divergence estimated by EWM, we can deduce the weights given to the PCI approaches. The overall value The steps following the equations above lead to a final value by the fusion of conventional triadic PCI estimates operated by the EWM. While satisfied with the specification of equations, we would like to see the case-by-case evaluations, also using the Equation (12), and verify if their estimates are stable.In the method described above, we compared the global entropy of PCI estimates with respect to the maximum lnn that  defined  Leibler  divergenIn the detailed calculation, KL divergence considers the difference between one experiment in comparison to the subsequent one. Integrating this specification in the EWM framework allows individual weights, adjustments, and an entropic value per triadic PCI estimate from the conventional appraisal system. This case-by-case estimate most importantly turns out to be a comparable basis for validation. The main condition of validation, in this context, is the trend that the value states converge for the same property. This makes sense, as the utility determining value state attributes are the same .We conducted an empirical demonstration to show the applicability of the conceptual foundations of the entropy method in understanding the meaning of the value state and its connections to the EWM. To illustrate this, we considered the real estate appraisal system and data on a single-family property taken from estimations in . The proWe used a decision matrix consisting of these ten experiments by three types of PCI responses to evaluate the value state of the subject property. The final step of this evaluation process was to arrive at a decision about the market value of the property to enable more decisions from multiple economic agents. As shown in We propose that these variations arise from the differing degrees of reliability embedded within traditional PCI methods, necessitating a final, objective adjustment in the last evaluation step, which we accomplish through the EWM. We also consider that these variations are influenced by the fact that economic agents negotiate and make decisions based on PCI observables, influenced by their personal knowledge, needs, goals, and various other factors (beyond property attributes) that emerge in different PCI transaction contexts. Additionally, the competition between PCI, during which the referential position of value state of the subject is considered by economic agents, might also contribute to the observed variations.In practice, only one of these responses is estimated, and even so, the estimation is mostly limited to two of the triadic conventional approaches (within the same response). This difficulty results from the quality of input data, not the evaluation methods used. For instance, for the 8th response, the expert can approximately assume a value of $362,000 by the SCA for the property by primarily considering price estimates, and while excluding estimates using CSA and ICA. The expert can also factor in the estimation of the cost method, but this involves the difficulty of weighing two estimations. In this case, the common estimation (response) would be either a simple average with equal weights for both methods  or different weights—for instance, 60% for the SCA and 40% for the CSA . As long as different weights of importance can be attributed to the three methods, then the expert can suggest, for instance, 60% for the SCA, 20% for the CSA and another 20% for the ICA . The problem here is the subjective weights of importance, which are attributed in this final step of evaluation and ensue value estimates, involving measurement bias and error. The real issue at this final step is thus finding the appropriate weights of these responses in triadic methods.As part of the intermediary steps of the EWM, we operated a linear normalization technique to make the experimental data of The most important step in this study is the computation of divergence, which has two critical applications. Firstly, it determines the reliability of each method; secondly, it allows us to estimate the adjustment amount needed to reach a final value for the subject. The less an approach requires adjustment at this final stage, the higher its priority in the final value estimation. Following the steps of equations specified in The estimation of a stable and final value state from the fusion of the triadic conventional methods based on their respective weights derived using the entropies in We could be tempted to add each of the adjustments to the diverging estimates at the last step of the conventional estimates in Starting from the same entropy estimates of The enhancement of EWM 1 by introducing a novel approach in EWM 2 enables us to produce case-by-case estimates while maintaining a comparable basis of results. This was achieved by incorporating the number of experiences in the entropy approach in a unique way. Rather than using a fixed number of experiences, we varied them from 1 to 10, for each case assuming that the information gain is highest with the first experience and subsequently decreases when new experiences are added, reducing the level of accessible information. The KL divergence has proven to be effective in meeting this requirement, as evidenced by the fact that the results for the 10 experiences are becoming closer to each other on a case-by-case basis and between the fused 10 final estimates.The Value-state information disclosure acts on the expectations and decisions of economic supply and demand side agents. Because of its probabilistic and dynamic nature, value state complicates the process of personal and expert evaluation. Existing PCI concepts, observables, and methods within the framework of the worldwide appraisal practice go through many technically detailed steps of computations and adjustments within each PCI approach. Though this appraisal system can produce valuable triadic estimates (competing opinions) on the value state of a specific property (the “subject”), the practice predominantly depends on a single approach. Usually, two out of the three PCI are considered, but it’s uncommon for all three to be utilized. Unfortunately, this introduces variance in value state estimations. PCI concepts, observables and approaches considered simultaneously provide a better estimation of the value state. This is the most crucial step of the appraisal system where the analytic and scientific acts of measuring value state begin, assuming that the technical processes in the previous steps of evaluation within each approach have been considered closely.In our current evaluation system, we can opt for either an exclusive or inclusive practice in providing a final point value state estimate for a subject property. In the exclusive practice, the prevalent argument is that one of the PCI approaches more accurately represents the value state due to richer active information. Alternatively, the inclusive practice could involve two or three approaches simultaneously, either assuming equal or variable weights in approximating the value state. In both cases, it’s essential for experts to provide objective, justifiable computations and explanations for the simultaneous weighting and adjustments of PCI approaches. Our work initiates from this final step of the evaluation system, where measuring the value state is the most challenging aspect. To overcome these limitations, we introduce and utilize the Entropy weighting method (EWM) in the final step of the evaluation system as a primary value measure in conjunction with conventional PCI methods.The use of the EWM offers an important advantage over traditional methods, such as average or weighted average provided by subjective experiences. The EWM objectively assesses the weight of each method and simultaneously fuses the market value estimates of conventional approaches for a reliable pointwise approximation of the value state. To systematize its integration, we empowered EWM capacity by considering the treatment of mutual entropy and operationalizing the process of adjustments of conventional estimates in the ultimate step of evaluation. The results we generated in this work with the help of entropy measure are satisfactory and demonstrate its accurate application in property estimation. Based on the entropy principles and connections to value state, EWM calculations finally provide a simple, versatile and integrative framework that clearly improves traditional methods, in accurately providing pointwise predictions as demonstrated in this paper. This innovative alternative will benefit numerous stakeholders, such as property owners, private investors, institutions and governments by reducing bias and errors in value state estimation. Enhancing the core of the evaluation practice by introducing an additional step boosts the robustness of the evaluation system for experts and increases public confidence in the system.Working with the results of the EWM, we remarked that it has the potential to further improve the current system of evaluation. In addition to this global approach that estimates a fused value for all the responses in the whole data, we also tried the EWM in case-by-case evaluations, adjusting each imperfect estimation of conventional approaches. For that, we needed to adjust the EWM and integrate the Kullback-Leibler divergence in relative entropies of each case in the data. This is an important technical contribution of our work as it not only allows a value estimate for each of the triadic estimates in the data, but it also provides a validation basis with all estimates showing a trend in their behavior that logically should converge to a constant value . This enhancement enables experts and cities, especially during mass evaluations, to justify the objectivity and reliability of the results.Real estate market prices are often established through negotiations between parties and possible intermediaries. Integrating EWM into conventional PCI methods to derive a point estimate might limit the flexibility of real estate markets, potentially reducing transaction volumes and long-term value states. Assuming the improved reliability of estimates by the PCI/EWM combination leaves less room for “entropic behaviors” from supply and demand side agents, creating higher risks but also opportunities. PCIs are compared and observed in the market, and future negotiations will likely become more adept over time, converging towards more stable market values. This hypothesis that emerges from the results of this work certainly deserves to be explored in future research.These global and case-by-case estimation results show that, unlike conventional methods, entropy can objectively detect and measure value state beyond what PCI attribute adjustments can do in the conventional process of estimations. In that respect, entropy more accurately considers the interplay between expectation and information in value states that are out of the reach of conventional methods. We have observed that there are certain subjective and unexplained aspects that exist beyond the variability of attributes that are not entirely captured by the variability of PCIs. Entropy accounts for PCI variance implicit in expert estimation, providing a wider and more appropriately approximating market value. From this perspective, this work illustrates the shared properties between entropy state and value state, which are vital considerations in Multi-criteria decision making (MCDM). We believe that illuminating these connections encourages the development of valuable research in this field.There is something more than what is explorable through these attribute adjustments and PCI information such as the explanation captured by mutual entropy on the dynamics of competing PCI formation, which are alien to conventional processes of individual attribute and PCI method adjustments. In fact, PCI conventional methods can consider all types of internal adjustments, quite well exhausting the potential information in each PCI estimate. Starting from these adjusted final estimates , entropy measures of value state show that there is significant incentive for more adjustments with EWM integrating mutual information correction and KL relative divergences. This mutual information contains the effects of interplays between competing PCI sales, cost production, and income exploitation agents under the governance of value state. What that means is that the value state should converge to a stable value state for every estimation of all potential methods for the same property . If that theoretically assumed convergence varies significantly, as was the case in our data of conventional estimates, it is because of their neglect of PCIs attempting to mutually reconcile their reward freed from the value state to which they all refer.Decision theory considers information as decreasing uncertainty, and entropy can be used to reduce uncertainty in the evaluation process in economics, especially within the field of real estate appraisal. Entropy naturally reflects the thoughts of economic agents who not only see the observable physical and economic indicators, but also the information they deduce as perceived value. It’s notable that entropy is closely related to the probabilistic state of value, with its mechanisms of expectations and information. It attracts the undisclosed (uncertain) portion of information in the object or event of desire, and these desires are human and non-algorithmic in nature. The desire to disclose this value is the source of motivation. As added information is revealed, the attraction to value diminishes until it disappears entirely. Expectation and information follow opposite patterns, with expectation decreasing as information is revealed, while information increases up to a maximum level where it equals the constant value for a given type of event or object. This interaction mirrors the properties of entropy, which also combines expectations and information. Information and entropy transform raw data, like PCI, into the essence of value, potentially addressing the limitations of statistical methods.In conclusion, this article wrestles with the question: Is the value of real estate an objective or subjective concept? Arguments for both perspectives are presented. On one side, there are compelling arguments suggesting objectivity in the value concept, determined by wider market agreement converging on a narrow range of values. However, from another viewpoint, information entropy indicates value as a subjective notion, one that cannot be completely defined. Analogously, our approach resonates with the method of value determination utilized in quantum economics . An appr


Nature Communications has finally confirmed the existence of topological defects in glasses and their crucial role for plasticity.Mixing theoretical topological structures with cutting-edge simulation methods, a recent study in  Nature Communications, which confirms the existence of defects in glasses and their crucial role for plasticity.Identifying topological defects in disordered materials has a profound effect on predicting when and where the material will break. Matteo Baggioli comments a recent publication in  In a crystalline solid, atoms are not randomly arranged. On the contrary, they sit in preferred positions, forming a periodic and ordered structure as depicted by the white sheeps in Fig. If all solids were similarly well-behaved, the life of a physicist would be rather boring. Nevertheless, many solids in Nature are amorphous, and they do not respect the ordered and periodic atomic arrangement described above. Glasses are the most famous example of that sort. The structure of a glass is disordered and more akin to the colorful and heterogeneous herd of sheeps shown in Fig. 1, the irreversible deformations which bring to the breakdown of the elastic response. In other words, they are critical to connect structure with dynamics, and to predict when and where a certain material will break. A common idea is that, even in glasses, plastic deformations take place in soft spots with abnormally low elastic constants and increased mobility, analogous to dislocations in crystalline systems. The remaining question is how to locate those weak zones from structural information, or even better how to relate them to the presence of defects which potentially control the plastic flow. In order to understand the difficulty behind this task, we need to dive into the mathematical tools that physicists use to define and quantify order and disorder.The reason why we should care about finding defects in that mess is very practical. In crystalline solids, defects play a fundamental role in predicting mechanical failure and the onset of plasticityTopological defects appear in many disparate areas of physics from cosmic strings in the universe, to vortices in superfluids and even in the patterns of human fingerprints. They represent a beautiful bridge between physics and a branch of mathematics known as topology. Given an ordered medium, like the sheeps in Fig. To avoid confusion, let us clarify that with the word topological we do not mean defects in coordination or in the number of neighbors, as sometimes used in the context of disordered materials. In the mathematical terms outlined above, those are not topological since they can be removed by a continuous transformation. Beside all the jargon, the main point is that the definition of defects necessitates the existence of an unbroken subset of symmetries that leaves the ground state of the system invariant. For crystalline solids, these are just the rigid translations of the ordered lattice. For amorphous systems, there is no remaining isotropy group. The whole shebang collapses from the start. To iterate the concept, a certain degree of order is needed to define disorder.2, and has been extensively scrutinized and questioned using theoretical arguments and numerical simulations5. Studies have shown that the properties of amorphous systems are undeniably structure sensitive and that regions of high stress and low symmetry, resembling dislocation cores in crystals, can be identified in glasses5.The search for topological defects in amorphous solids has a long and controversial history. The idea that dislocations lines could exist in glasses is almost 50 years old6 concluded that most of these indicators are excellent at locating plastic events over short strain scales, but they do not provide a first principles understanding of plasticity, as in crystals. On the other hand, several successful theories such as shear transformation zones7, and elasto-plastic models8, have postulated the existence of such defects without any precise definition.The conviction that plasticity in glasses could still be related to structure led to the introduction of a plethora of structural, thermodynamic and mechanical indicators, including the local shear modulus, energetically favoured regions, linear and non-linear vibrational modes, local thermal energy and more abstract measures of softness. A throughout study9 was to hunt for defects in the dynamical displacement field rather than in the static structure, and look for singularities upon deforming the system. The inspiration came by thinking about the incompatibility of the deformation, which naturally arises because of non-affinity, and which can be related using mathematical objects known as higher-form symmetries to a strain-free formulation of elasticity10. The results of ref. 9 indicated that standard topological concepts applied to the dynamical displacement field allow for a precise identification of defects, which well correlate with the major plastic events and successfully predict the location of the global yielding instability.Against this background, one could just rely on these successful but phenomenological structural indicators or search for defects in glasses beyond their real-space structure. This second choice is what all these new developments are about. The first idea in ref. 9 gave up on probing the static structure. In other words, the problem of relating structural defects to dynamics was bypassed focusing only on the dynamics itself. That was still unsatisfactory, until Wu and colleagues’ recent paper, published in Nature Communications11, came out and provided a potential breakthrough in this story.Still, the study in ref. 11 discovered that the long sought structural defects in glasses were hiding in the topology of the vibrational eigenmodes. Differently from the original idea of Baggioli et al.9, that is still a property of the static and undeformed configuration, but not of the real-space structure. Wu and colleagues noticed that the spatial distribution of the eigenvectors display a collection of whirls and curls and eye-visible vortex structures (see Fig. 7. In Fig. Wu and colleaguessee Fig. b, with m11 managed for the first time to identify topological defects in the static structure of glasses and to provide a direct link between the properties of glasses before deformation and the plastic behavior during it. As for the case of dislocations in crystalline solids, this realizes a connection between structure and dynamics in amorphous systems which goes far beyond all the phenomenological structural indicators considered before and highlights the role of topology and geometry in the context of disordered systems and their plastic behavior.To make it short, Wu and colleagues12, and the vortex-like formations possibly constituting the shear transformation zones in glasses13. Finally, these defects could be formally related to geometric charges in the metric formulation of elasticity14, and to magnetic currents in the gauge theories for emergent elasticity in granular matter15.The revealed topological information displays striking similarities with the quadrupolar Eshelby-like structures believed to be fundamental for the plasticity of amorphous solidsIn summary, the topological defects discovered by Wu and colleagues could play a pivotal role in our understanding of glasses, from the boson peak feud, to the nature of the glass transition as a topological phase transition, up to the fundamental origin of yielding. We just need to sit with a coffee mug and a doughnut and wait to see how topology will help us to make order out of disorder.


Biobanks are essential structures for scientific research. The RHINEVIT biobank is used to recruit biomaterials from rheumatology patients in outpatient care and to conduct clinical research studies  and basic research. RHINEVIT established Broad Consents (BC) to allow extensive and relevant usage of data and biospecimens without the need for specific project restrictions. For quality assurance, we compared the consent rate of individual items of the BC versions in patients with systemic lupus erythematosus (SLE) in the longitudinal study.BCs were used for biomaterial donation. Informed consent data from RHINEVIT were analyzed. Due to the content restructuring of the BC items due to changes from the templates of the working group of the Medical Ethics Commissions in the Federal Republic of Germany and GDPR requirements, content mapping of the items was performed for the analysis.From September 2015 to March 2022, 291 SLE outpatients donated biomaterials. In 119 patients, the BC was renewed at least once in a subsequent biomaterial donation. Three biomaterial donations were obtained from 21 patients and four from six patients using the respective BC. However, one consent was later revoked. Consent to the BC topics showed consistently high rates of agreement (range 97.5%−100%), with only some patients disagreeing with individual topics. This remained stable over time . None of the patients disagreed with a certain topic in two consecutive visits.Modifications to the BC did not result in any relevant changes in the approval rates for SLE patients. RHINEVIT's BC is successfully used for the quality-assured handling of excellently annotated biomaterial. The long-term use of these highly valuable biospecimens for unrestricted research, also in an international context, remains assured. Dedicated biobanks provide the opportunity to collect and store well-annotated human biomaterials for long periods of time. Their significance for modern medical research is still expanding, not only in “large, centralized high-quality biobanks” but also in those of clinical departments with specialized foci –3. BiomaRheumatology biobanks may be used for the assessment of personalized treatment options . Since 2Apart from study-by-study consent, RHINEVIT established a Broad Consent (BC) for biomaterial collection to assure modern, ethically acceptable biobanking . This apResearch on BC use in biobanking in IRDs is scarce, although there is an overarching need for a practice evaluation of BCs to improve their validity and applicability . Thus, fSince 2010, the Biobank RHINEVIT has used the certified biobanking software Genomatch University . The software complies with the necessary international standards, such as 21 CFR Part 11, Good Clinical Practice, and Good Laboratory Practice, and thus enables regulatory compliance for biobanking .For the purpose of biomaterial collection in our routine outpatient clinic, BCs based on the templates of the “Arbeitskreis Medizinischer Ethikkommissionen in der Bundesrepublik Deutschland e.V.”  have been established as a governance procedure since 2014 . Owing tWhen biomaterials were collected, the patient's information leaflet regarding the research scope of the biobank and its implemented procedures , and consent forms were handed out as paper-based versions. Patients read the patient's information and considered their consent while waiting in the waiting room or in the outpatients' treatment room. Written informed consent was obtained by the treating rheumatologist or a member of the RHINEVIT biobank team. A signed copy was given to the patient to take the informed consent home. When a subsequent biomaterial collection was performed on an individual patient, the BC was renewed and entered into the software accordingly.So far, the biobank stores only biomaterial taken in addition to blood for analyses within the scheduled routine outpatients' visits or in addition to non-biobank-exclusive research studies and does not store residual biospecimens  , 20, 21.An informed consent form was prepared for appropriate pseudonymization using patient's identifiers from the hospital information system and a pseudonym that was created for use within the biobanking software architecture (“Barcode 1”). This barcode 1 was also used for labeling the biomaterials to ensure that the information from the consent form and the biomaterials could be linked together appropriately.Signed paper-based forms were entered manually by a trustee into the biobanking software via the provided trustee dashboard. It includes functionality to assign patients' identifying numbers  to the pseudonym (Barcode 1) and the current version of the informed consent. Annotating clinical parameters were derived from our web-based patient documentation system, DocuMed.rh . PatientThe use of BC in the context of the RHINEVIT biobank received its first positive ethical vote from the local ethics committee in 2014 (Number 4711) and was renewed with the updated BC versions. Studies with biomaterials were registered with the German Clinical Trials Register, where applicable.For quality assurance purposes, data from three versions of informed BCs from the period of September 2015 until March 2022 were extracted from the biobank database. The consent options of the versions were mapped to each other to guarantee the comparability of items.None of the BC items distinguished between genetic, serological, and/or clinical parameters that affect or derive from the biomaterials. However, patients were informed in the patient's information that genetic data or examinations might be performed.*) were asked for their informed consent for RHINEVIT on a longitudinal basis in our outpatient clinic, we analyzed their responses to the Broad Consents.As most patients with systemic lupus erythematosus . The median disease duration was 15 years. Further clinical characteristics of the cohort are presented in In a total of 119 patients , consent was renewed for subsequent biomaterial collections at least once. Hereby, we identified 21 patients with three and six patients with four biomaterial collections, resulting in 443 Broad Consents. Only one consent was revoked for unknown reason(s).n = 4) vs. 46.8% (n = 132), p-value Fisher exact test: 0.04].Regarding the differences in clinical characteristics between patients who gave consent to all items and those who refused some items, we observed that most characteristics are similar in both groups. Only for the education level, a significant difference was identified, with those who refused at least one item having a higher level of education (a university degree) at a higher rate . The consent rate for the detailed items of the BCs was slightly lower on the second visit date but remained at a very high level, with at least 97.5% for each item. None of the patients disagreed on a certain topic on two consecutive visits.To the best of our knowledge, our study is the first to focus on the individual BC in a rheumatology biobank embedded in routine care. The various aspects of our established RHINEVIT BCs that were and are based on the template of the Medical Ethics Commissions in the Federal Republic of Germany were well accepted by our predominantly female SLE patients, also over time with the changing BCs. This is in contrast to recent findings from a survey among participants in a large DNA biobank, where the authors conclude that biobank participants' preferences regarding sample use may change over time and consent stability cannot be taken for granted . They alOur biomaterial donors that consented to all BC items are of middle age, while those denying some items were a little younger see . This isBiomaterial donation and the future of biobanking research also heavily rely on trust in biobank owners and the relationship with the researcher –28. Althn = 650) that the belief that every citizen has a duty to contribute to the improvement of medical research is the strongest predictor of positive attitudes toward data donation  , 33, allHowever, that understanding and the resulting opinion require extensive health literacy and individual knowledge that cannot be taken for granted. Furthermore, contextual demographic, cultural, and sociopolitical factors need to be taken into account . (e)HealUnfortunately, apart from publications naming biobanks –42, to dRecently, the RHINEVIT BC was updated, allowing the storage of additional skin biopsies. Further efforts to include other biomaterials, such as kidney biopsies, are ongoing. Since additional annotations of biomaterials from other data sources, such as laboratory tests from primary care physicians, orthopedic surgeons, or dermatologists, can be highly valuable for biomaterials in biobanks, the implementation of these further annotation possibilities for RHINEVIT will be sought in the future.Our patients extensive support of research gives us high flexibility for performing our research with biobanked biomaterials. However, it is fundamental to implement and actively use policies on biomaterials and annotating data sharing that relate to ethical, legal, and societal issues (ELSI) and also meet the specifications of the institutional review boards . TypicalIn this study, predominantly female patients with SLE were studied at a tertiary rheumatology center. Further studies involving more men and other IRDs are needed. The majority of patients were asked to donate additional biomaterial as co-consent for a clinical research study. In addition, we did not investigate why patients gave or withheld their consent and do not yet have a picture of patients' understanding of the contents of our BCs. RHINEVIT does not yet systematically assess if patients have an interest in results emerging from biobank activities. These issues need to be addressed in further research.The modifications made to the template text of the Working Group of the Medical Ethics Commissions in the Federal Republic of Germany and the resulting adaptations of the BC have not led to any relevant changes so far in the consent rates for SLE patients participating in RHINEVIT. Thus, our BCs have been and are successfully used for quality-assured handling of excellently annotated biomaterials from routine care. The study showed that there is a high willingness among our patients to consent to the  collection of biomaterials and the use of their data collected within routine care for research, even in the context of a BC and without pre-specified research aims. Further research on patients' preferences that also assesses the practicability and acceptability of electronic infrastructures to support the contact of participants and dynamic consents in biobanks is warranted.The data supporting the conclusions of this article are available on reasonable request by the authors.The study was conducted under the approval of the Ethics Committee of Medical Faculty at Heinrich-Heine-University Duesseldorf for the biobank, local study number 4711. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.All authors were involved in the biobank project, made substantial contributions to the conception and design of the work, the acquisition, analysis, and interpretation of the work, developed the manuscript, and approved the final draft.


Zinc is essential for several biological processes including those critical for the immune system, DNA synthesis, cell division, and growth. Zinc is involved in the pathophysiology of chronic diseases and protects proteins and lipids from oxidative damage. Inadequate zinc intake and low plasma zinc concentration are associated to an increased risk of chronic diseases such as cardiovascular diseases and type 2 diabetes; however, the evidence is limited. Zinc deficiency increases the risk of infections and poor growth and may contribute to the high burden of infectious diseases and stunting in children living in low- and middle-income countries. The risk of zinc deficiency in the populations of the Nordic and Baltic countries is low. Zinc has a wide range of crucial physiological functions and is present in every cell in the human body.No reliable biomarker of zinc status has been established.Severe zinc deficiency increases susceptibility to infections, poor growth, poor wound healing, hair loss, anorexia, altered taste, skin lesions, and eczema.The consequences of mild or moderate zinc deficiency are unclear.Meat, dairy products, legumes, eggs, fish, and cereals are good food sources of zinc.Bioavailability of zinc is affected by the intake of phytate and calcium.Zinc is essential for DNA synthesis, cell division, and the normal functioning of the immune system . Zinc isBox 1Background papers for Nordic Nutrition Recommendations 2023This paper is one of many scoping reviews commissioned as part of the Nordic Nutrition Recommendations 2023 (NNR2023) project The papers are included in the extended NNR2023 report, but, for transparency, these scoping reviews are also published in Food & Nutrition ResearchThe scoping reviews have been peer reviewed by independent experts in the research field according to the standard procedures of the journalThe scoping reviews have also been subjected to public consultations (see the report to be published by the NNR2023 project)The NNR2023 committee has served as the editorial boardWhile these papers are the main fundament, the NNR2023 committee has the sole responsibility for setting dietary reference values in the NNR2023 project.de novo systematic review and no qualified systematic review on zinc was identified by the NNR project .2+). It has a wide range of vital physiological functions and is present in every cell in the human body  were estimated based on daily losses through the kidneys, skin, semen, or menses and the gastrointestinal tract (faeces). The dietary requirement is also dependent on the fraction of zinc absorbed from the diet. Fractional zinc absorption is dependent on zinc content; when intakes are increased, the proportion absorbed decreases. The composition of other nutrients in the diet will also affect the fraction of zinc absorbed. At low intakes of zinc in diets with no inhibitors, the fractional absorption can be >50%, but the fraction can be as low as 10% . In NNR2It is possible that a more plant-based diet with a higher content of chelating substances such as phytic acid and tannins may increase zinc requirements. Furthermore, since animal-source foods are the main sources of zinc, a shift to a predominant plant-based diet might result in lower mean intakes and a higher proportion of the population that falls below the AR. It should be noted, however, that the risk of deficiency in the Nordic and Baltic countries is low. In 2014, EFSA updated their DRVs for zinc and provided adjusted population reference intakes (PRI) according to the intake of phytic acid . In thisThere is insufficient data on the endogenous losses of zinc at different intakes for children. The zinc requirements for adequate growth are approximately 175 µg/kg/day during the first month and then approximately 30 µg/kg/day for the next 9–12 months . For groThe total need for zinc during pregnancy for the foetus, placenta, and other tissues is approximately 100 mg . This adThe zinc content in breast milk is approximately 2.5 mg/L in the first month of lactation and decreases to about 0.7 mg/L after 4 months . This meThe DRVs for zinc vary between countries and regions, which reflects the uncertainties in the DRV estimates. This variability is, in part, due to the variability in fractional absorption and uncertainty related to the health consequences of mild to moderate zinc deficiency. The consequences of mild or moderate zinc deficiency and the identification of reliable biomarkers for zinc status are important knowledge gaps. Furthermore, it is expected that the intake of animal-source foods will decrease, and how this will influence zinc status and the risk for zinc deficiency in the Nordic and Baltic countries is an important research question.


In today’s rapidly changing economy, efficient lifestyle has become the current situation of most mobile product users. With the development of performance tools and technologies, a fast lifestyle has brought more wealth and opportunities to users. The slow pace and fluctuating time are indirect income losses, which cause user anxiety to some extent. When the waiting time exceeds the user’s waiting threshold, users would experience negative emotions, such as boredom, anxiety and anger, and product satisfaction would drop significantly. Therefore, by analyzing the uniqueness of mobile Internet products and the characteristics of users, this paper studied the reasons and influencing factors of product interactive waiting, and then used machine learning algorithm to analyze the cost function of interactive waiting experience. Finally, the corresponding interactive waiting experience design strategy was proposed. By comparison, the user experience after product interaction optimization design was 8.4% higher than that before product interaction optimization design, and the user frequency was also 14.7% higher after optimization design. In short, user experience plays an important role in product interaction design. With the rapid development of smart devices and mobile applications, the portability and miniaturization of mobile Internet products have been supported by most users, creating a huge space for mobile application development. Due to the uneven configuration of mobile devices and a large number of information processing algorithms, waiting for information on the page is a major challenge for users. At the same time, in the context of rapid improvement of information processing technology and hardware performance, users have increasingly high requirements for interaction with applications. Therefore, the design of interactive products not only focuses on the structure and organization of the elements of the software itself, but also focuses on the changes of users’ behavior and emotion in the process of use.1. Sousa Rui studied the relationship between product customization and service strategy, especially the relationship between the strength of product customization strategy and the degree of service, and the regulatory effect of product customization strategy consistency on this relationship2. Petit Olivia believed that sensory marketing in the digital environment can provide a richer online experience, which was expected to open the way for further research and development in this field3. Hoyer Wayne D provided a new type of AI driven new technology to manage these new AI technologies along the customer experience dimension to create experience value4. Bleier Alexander examined the role of unique design elements in shaping the four dimensions of the online customer experience. Product experience and brand reputation characteristics exacerbate or reduce the inherent uncertainty of online shopping, thereby reducing the impact of various experience dimensions on purchases5. Izogo Ernest Emeka provided a comprehensive and dynamic customer experience model, covering all stages of the customer decision-making process. By drawing on new theoretical perspectives, he demonstrated the unique properties of the online shopping experience that contributed to existing research on customer experience6. Chen Ja-Shen proposed a research model based on technology acceptance model and information system success model to describe the relationship among chat robot adoption, online customer experience and customer satisfaction7. The above studies have described the importance of user experience, but there are still some deficiencies in interactive waiting experience.User experience plays an important guiding role in product design. Tao Fei proposed a new method of product design based on the digital twin method, introduced the development of product design, and then proposed and analyzed the framework of digital twin-driven product design8. Yi Shanshan applied machine learning algorithm to analyze product information and store information based on customer experience learning, and collected product data with customer comments from the benchmark unified computing system9. Chi-Hsien Kuo built a machine learning model to help minimize research barriers, and proposed an unsupervised end-to-end model that can directly and accurately handle user experience effects without human intervention10. Liu Lina used ontology to build a user knowledge model, integrated multiple situational similarity indicators, and studied the artistic design of user interaction experience in mobile systems through situational awareness and machine learning methods11. The above studies have described the user experience effect, but not the experience design strategy.Many scholars have studied machine learning and analyzed the quality of user experience. Nwakanma Cosmas Ifeanyi outlined the potential of using natural language processing systems to classify user experience quality, and developed an improved regression classifier to test, train and classify user experienceIn order to study the interactive waiting experience of mobile internet products, this paper analyzed and studied the cost function of interactive waiting experience through machine learning, and then analyzed the factors of interactive waiting experience. Finally, the strategy was proposed and experimental analysis was carried out. According to the experimental analysis, users were satisfied with the optimization of interactive waiting experience design, and the waiting time and user experience have been greatly improved. Compared with other literature, this paper focused on the use of experimental analysis of user waiting time and experience before and after optimization.12. Secondly, the waiting status of mobile internet products is different from that of network products. Compared with Internet products, the interactive waiting state of the mobile Internet has the following characteristics, but users’ tolerance for the waiting state of mobile products is lower than that of Internet products, making the waiting state of mobile products mainly short-term downloads. Compared with various operation modes that need to be executed on the website (such as downloading and a large amount of information input), mobile internet products use output type as the main operation mode and read related operations as the main behavior, so most of the download operations occur on page separators and content downloads.The uniqueness of mobile internet products can be analyzed from two aspects. The first is the difference between mobile internet and website. Mobile Internet has the characteristics of mobility, real-time, accuracy and positioning. Compared with network products with fixed network location and fixed network as the main scenarios, the use scenarios of mobile internet products are very diverse. The transmission environment and size of mobile internet products are limited to networks and terminals, processing capacity and battery capacity. Therefore, the difference between mobile internet and web pages is that mobile internet takes mobile scenario as its main use scenario. Users can use any operation at anytime and anywhere, and the functions of mobile products are always easy to distribute and centralize information. Customers are segmented according to participation and use of discretion while paying attention to the satisfaction level of different market segments13. Social software can chat with friends at anytime and anywhere. The most important thing is to spread information. A good user experience can increase the number of users.According to the analysis of users using mobile internet products, these users have common characteristics, as shown in Fig. Although mobile Internet hardware and related technologies continue to develop rapidly, every technological progress is determined by users, and the huge development of technical capabilities is always accompanied by huge demand. When the requirements are not met, the technology use process would occur, resulting in the “waiting” phenomenon. The reasons can be summarized as two points, as shown in Fig. First, the performance of software and hardware should not match the interactive waiting state caused by data requirements. Secondly, the mobile product design capacity is insufficient. In the first case, people can not only improve this situation by investing in software and hardware, but also fundamentally solve the problem by improving the system algorithm and the system architecture of development information and user cognitive verification. People can design interventions to improve the user’s waiting experience. For the latter, business, process, logic, behavior, vision and other elements waiting for interactive design can be developed to optimize the whole work.As for the appearance of interactive waiting state, due to the difference of system performance, its existence cannot be recognized. In addition, interactive waiting should not be regarded as a waste of time and a reduction of product user experience. The designer pays attention to the humanized user experience perspective, optimizes the detailed waiting chain, alleviates users’ concerns through online applications and reviews the online waiting status. The standby state must be friendly designed to adapt to the user environment. Frequently, long wait and other unplanned wait can affect the design scenario, which needs to be optimized and improved. The objective performance of hardware and software directly determines the work efficiency of users when using mobile products. Better hardware quality and optimized software algorithms can effectively shorten the waiting time of users when using products and improve the use efficiency.The factors affecting the interactive waiting of mobile Internet products are mainly divided into two categories, as shown in Fig. The first is the cognitive node of the interaction process. Once users are stimulated by information on the interface, they would develop knowledge about the interface, and the interface would understand feedback and cooperate with them. The expectation of mobile products depends on all these cognitive processes. If it is difficult to read the interface information at the sensitive stage of the interface content, the efficiency of users accessing information through the interface would be greatly reduced, which would affect the interaction efficiency. The user’s understanding of information is mobile, which directly affects the interaction efficiency of the product and the understanding and readability of the content. Users can quickly log in and run links, improve the interaction efficiency, reasonably apply interdisciplinary knowledge and technology, optimize the interaction waiting process, and make users feel humanized when using the system. Effective feedback has a great impact on the next interaction process. It hinders the interaction between users and the expected psychology of interaction, and increases the proportion of expected information in the interaction feedback.The second is the content of interaction design. If there is no reasonable and humanized practical planning, it would lead to users’ perception of product information and related logic, which can affect the efficiency before user interaction, and thus affect the entire interaction process. This would lead to the passivation and maintenance of the map in the process of user interaction. The process of high-level data translation would directly affect the efficiency of user interaction. Due to the imperfect design, users inevitably show a “slow” and “stuck” cognitive waiting state before interaction, which would have a negative impact on the entire interaction process.There are two types of interactive waiting time: physical waiting time and psychological waiting time, as shown in Fig. The objective factor is mainly the factor that the application product takes time to download, such as the network environment where the mobile device is located, mobile equipment installation, etc. All these processes would affect the software download time. Due to the uncertainty and technical limitations associated with the use of mobile products, it is often difficult to eliminate delays. For example, the background architecture method and other methods objectively affect the waiting time of users.14. Negative emotions would make users feel that the waiting time is longer than the actual time, thus further intensifying the negative emotions of users.The subjective factor is mainly the personal factor that affects the perception of download time when using the product. The user’s perception of waiting time caused by the subjective factor is usually called waiting time perception, that is to say, compared with the actual waiting time, it is the duration of the user’s subjective psychological perception. The understanding of waiting time is generally slightly different from the actual waiting time. On the one hand, these differences are affected by subjective factors. On the other hand, this in turn would have a negative impact on users, which would have some emotional impact on users. For people with high desire for control, products have a stronger positive impact on user experienceCommon factors that affect users’ awareness of waiting time include emotion prolongs users’ awareness of waiting time. The user is busy performing urgent tasks, and the application feedback time is short, which affects the user’s understanding of the actual waiting time. Users who are familiar with the application may have relatively accurate psychological expectations, while users who are not familiar with the application may have higher expectations. These different psychological expectations directly affect their perception of application feedback time. When users wait for a long time, users would have negative emotions, which would affect their satisfaction with the product. These negative emotions would affect their perception of expectations. The longer the waiting time, the lower the user satisfaction with the product and the worse the user environment. The shorter the detection waiting time, the higher the user satisfaction with the product, and the better the user experience. If the perceived waiting time of users is less than the actual waiting time, their satisfaction with mobile products would be significantly improved.Machine learning is a multidisciplinary discipline, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and many other disciplines. It specializes in the study of how computers simulate or implement human learning behaviors to acquire new knowledge or skills, reorganize existing knowledge structures, and continuously improve their own performance. Machine learning algorithms can be classified according to different criteria. For example, according to the function f , machine learning algorithms can be divided into linear models and nonlinear models. The machine learning algorithm used in this paper analyzes the cost function of interactive waiting experience.15. First, this paper calculates the asymmetric probability in the interactive waiting experience as follows:In order to study the design effect of interactive waiting experience of mobile internet products, this paper analyzes the asymmetric probability and Euclidean distance in interactive waiting experience through machine learning algorithm, and then obtains the waiting probability and cost function of product interactive waiting experience designAmong them, k is the constant set manually, and Among them, The cost cost function is to measure the specific application effect of mobile Internet in product interactive waiting experience design, and evaluate the product interactive waiting experience design according to the change of cost function value before and after the use of mobile Internet.Through the interactive waiting cost function analyzed by machine learning algorithm, this paper proposed the following design strategies to optimize the interactive waiting experience of products. Based on the analysis of the influencing factors of interactive waiting experience, machine learning is used to analyze the cost function of interactive waiting experience, and then optimized design is carried out to improve the interactive waiting experience and shorten the waiting time of users.16. If the user encounters any problem without interface feedback, the waiting process is monotonous, and the loading state and loading time are unknown, which directly leads to the user’s illusion of time estimation and prolongs the perception of waiting time. It returns to the page in an empty standby state, and displays the working status and the exact time when the user page loads in the background in the form of text or pictures, reflecting the current loading status and loading level. The waiting time can be determined in advance, thus reducing the change of user mood to an unknown state. Effective provision also facilitates the report on page loading status and the multi-channel communication model for downloading information to a certain extent.When the product loading page, the user cannot detect the background operation and data loading process of the productDuring the user waiting period, in addition to the user’s immediate feedback on the product function, other negative emotions would be encountered, such as anxiety, fatigue and others. In order to meet the needs of users, designers often upload some content to help users browse the next page, so as to reduce the negative emotions caused by waiting and reduce users’ perception of time. In addition, the download speed is accelerated by reducing the quality of images or videos, and the data is downloaded gradually during viewing to ensure a smooth user experience.17. In addition, there is a simple version of the system, which can directly develop the entire software set. In other words, application developers can remove complex and rare functions and only retain the basic functions that users usually use. By observing the concept of humanized design, and weighing advantages and disadvantages, they can make appropriate decisions to effectively improve the user experience.If the user’s network environment is poor or the hardware configuration is low, the waiting time for application interaction is far longer than normal interaction, but these objective factors would not reduce the user experience or hinder normal use. It is recommended to further optimize the current online waiting. It is necessary to delete images and videos downloaded for a long time, or change the appearance of simple applications to reduce the quality of downloaded imagesIf the interactive waiting time is much longer than the user’s expectation, the user would have the idea of giving up waiting. Their efforts would not get a quick response, and their hearts would inevitably be unbalanced, which can measure whether it is necessary to wait for rewards. Once experiencing the product, all users can remember to start and end the experience. The proportion of good and bad experiences and the duration of the experience have a relatively small impact on the user’s memory. Therefore, compensating interactive waiting time can create human experience at the peak time of user waiting period, compensate user’s psychological bias, and reduce the impact of excessive waiting on user’s mood.18. In order to be truly user-centric, designers must put themselves in the scene where users are waiting, and experience users’ feelings and perceptions through observation, understanding, expected behavior and operating habits. Then the corresponding interactive waiting design is carried out to provide users with a more convenient experience.The user waiting time needs to be reduced. The application interface shows users how to predict the waiting time in advance and improve user satisfaction through interactive waiting. Interactive waiting should also focus on the concept of user experience design, and interactive waiting design must follow the user-oriented experience. From the perspective of system self-awareness and user interaction, it conforms to the user’s usage habits, expected interaction mode and corresponding psychological experience in a larger range. The effect of customer participation is created by enhancing gender voice and product intelligenceThe first step is to understand the user community. The user group here includes different users’ age, educational background, occupation, region and other factors. By understanding user groups, product design and interaction can be optimized according to their needs, habits, cognitive abilities, etc. Secondly, in the process of product interaction design, it should pay attention to concise and clear operation steps. An excellent Internet product should avoid lengthy and complex operations as much as possible, so that users can quickly and simply achieve the desired results when using it. At the same time, users should also be able to clearly understand the process and results of each step when interacting, so as to improve the operability of the product. Thirdly, product design should pay attention to record the user’s history of use records and behavior habits. This is conducive to establishing a more intimate connection with the user, and it can also be personalized and recommended in the subsequent design. Finally, a good Internet product should be differentiated as much as possible to highlight the features, so that users are easier to distinguish and remember. In all kinds of imitation and homogenization of the market, only products with characteristics can attract more users, so as to enhance the market competitiveness of products. For example, when King Glory matches players waiting to enter the game, Tencent gave some game guides in the interface to attract users’ attention and reduced the user’s feeling of waiting.In order to study the design effect of interactive waiting experience of mobile internet products, this paper analyzed the cost function of interactive waiting experience through machine learning, then compared the proportion of waiting time and information feedback effect before and after optimization, and finally compared the user experience and user use frequency before and after optimization. To this end, this paper first investigated the satisfaction of users in three regions after the interactive waiting design, including 50 people in each region. In this experiment, the traditional product interaction waiting experience is before optimization, and the optimized product interaction waiting experience design is under mobile Internet. The specific results are shown in Table By comparing the difference between the sample observations and the hypothesized population parameters, a statistic is calculated, and based on that statistic, a p-value is calculated to evaluate how credible the observations are under the hypothesis. If the p-value is less than a pre-set significance level , the hypothesis is rejected as a significant difference in observations. It can be clearly seen from Table According to the data described in Table Figure Figure Figure Through the comparative analysis of the experiment, it can be seen that after the interactive waiting experience optimization of mobile Internet products, the user’s sense of experience is enhanced. Its use frequency is also more frequent, and the user’s demand is stronger. Moreover, after the optimization of product interaction, the information feedback effect and hardware skill problems have been solved and improved. To a certain extent, the user’s tolerance for the product has also been improved, and the user who has waited for a long time can be compensated in time, thus reducing the user’s complaint rate.Due to the objective factors when mobile applications interact with users, interactive waiting is inevitable. This article introduced the user interaction feature of waiting for feedback when using mobile applications. During the interactive waiting period, if the user can actively control the required waiting process and successfully complete the specified work task, the user can move on, control and continue at any time, and can feel the right to terminate and callback. The user would have a better feeling when waiting for the experience. Only by deeply understanding the user characteristics of mobile Internet products can they develop mobile Internet products that meet the needs of modern users. When designing the user experience environment, people can ensure consistent and personalized use and provide help and information to users in time.


Exposure notification applications (ENAs) or digital proximity tracing apps were used in several countries during the COVID-19 pandemic. In this viewpoint, we share our experience of implementing and running the Finnish ENA (Koronavilkku), one of the national ENAs with the highest proportion of users during the pandemic. With the aim of strengthening public trust and increasing app uptake, there was a strong prioritization of privacy and data security for the end user throughout the ENA development. This, in turn, limited the use of the app as a tool for health care professionals and deeper insight into its potential effectiveness. The ENA was designed to supplement conventional contact tracing, rather than replace it, and to serve as an early warning system and a trigger for action for the user in case of potential exposure. The predefined target of 40% uptake in the population was achieved within 3 months of the ENA launch. We consider easy-to-understand information produced together with communication experts crucial during the changing pandemic situation. This information educated people about the app as one component in mitigating the pandemic. As the pandemic and its mitigation evolved, the ENA also needed adapting and updating. A few months after its launch, Finland joined European interoperability, which allowed the ENA to share information with ENAs of other countries. We added automatic token issuing to the ENA as of mid-2021. If added earlier and more comprehensively, automatization could have more effectively saved resources in health care services and prevented overburdening contact tracing teams, while also notifying potentially exposed individuals quicker and more reliably. In the spring of 2021, the number of active apps started to gradually decline. Quarantine and testing practices for asymptomatic vaccinated individuals following exposure to the virus were eased and home tests became more common, eventually replacing laboratory testing for much of the population. Taken together, this led to decreased token issuance, which weakened the potential public health usefulness of the app. A self-service option for token issuance would likely have prolonged the lifespan of the app. The ENA was discontinued in mid-2022. Regularly conducted surveys would have helped gain timely knowledge on the use and effectiveness of the app for better responding to the changing needs during the pandemic. Large-scale rollouts of digital proximity tracing (DPT) and exposure notification apps (ENAs) were undertaken hastily in several countries during the COVID-19 pandemic. It is important to gather and document the lessons learned in the process for possible similar situations in the future. In this viewpoint, we share our experiences of implementing and running the Finnish ENA (Koronavilkku). We base our account on the first-hand experiences of developing and maintaining the national ENA that were discussed at the final project workshop. We refer to feedback received from the public, health care professionals, and decision makers during the app’s lifetime.SARS-CoV-2 started to spread in the Finnish population at the end of February 2020 . Like inAccording to the temporary law, the Finnish app would be voluntary and free for the public to use . These pThe Finnish app was divided into a mobile app and a backend system . The mobBased on early simulated models on potential for infection control ,15, a hiThe app was designed to supplement conventional contact tracing, rather than replace it, and to serve as an early warning system and a trigger for end user action. The aim was that upon receiving an exposure notification, the user would change his or her behavior according to the guidance given by the app, and thus, break transmission chains . The insAlready in the planning stage, it was decided that we should emphasize privacy and maximize app uptake, which imposed limits on the development but gave a clear focus to the work. After the launch, several independent data security experts, including the National Cybersecurity Center, evaluated the app against the privacy concerns that had been discussed in the media ,18. We bIn most EU countries, ENAs were developed in collaboration between governmental institutions and private software developers . This waTo support the project group, we set up an expert group of communicable disease physicians representing different municipalities and hospital districts. The group lacked decision-making power, but it was an important organ for keeping in touch with the health care services, where contact tracing was conducted and app tokens issued. The group was informed about the development and consulted on guidance and the calculation of risk factor parameters. The aim was to keep the parameters that defined possible exposure and recommendations in the exposure notifications in line with the national guidelines.From the start, communication experts planned how to share easy-to-understand information about the ENA with the public. As identified elsewhere, end user benefits of an app and clarifications on how individual privacy will be protected are important to communicate . CommuniFinland approached advertising the app as part of a bigger strategy against the pandemic and started informing the public about the app at an early stage . HoweverThe Finnish ENA was published in late summer 2020 , simultaThe ENA could be used in the 2 official languages of Finland, Finnish and Swedish, and additionally in English. However, some groups were not as frequent users of the app as the general population , and makThe ENA was developed on the premise that it would be a short-term app requiring no further releases. In Finland, the legal mandates of several control and mitigation measures related to the COVID-19 pandemic were temporary. If needed, the validity of these laws was extended; during the app’s lifetime, its legal basis was extended twice. In the changing pandemic situation, several changes were required in the app.The project received numerous requests for minor changes and ideas for implementation, and we needed an unbiased method for prioritization and approval of them. Through the use of a structured form, we identified which parts of the app, its backend system or linked information, would be affected; the time and effort required to implement the change; and the estimated public health impact. This helped us reach informed decisions on what to implement.In the fall of 2020, the national recommendation on quarantine duration was shortened from 14 days to 10 days. In line with this, changes in the app were required, so the duration an exposure notification was visible to the user corresponded with the updated guidelines. Similar changes were implemented 3 times during the lifetime of the app. Other updates were also made, such as a modification to exposure calculations to consider all exposures over the course of a day and changes to the interface to make it more user-friendly; these changes included displaying the number of potential exposures and adding a button to manually launch exposure checking. The motivation for all these updates was to keep the ENA current, attractive, and easy to use, thereby enabling its intended public health impact.Several European countries launched their own mobile proximity contact tracing and warning apps, and an effort to explore sharing exposure notifications across apps was pursued by the European Commission and the member states . In ApriIn accordance with increased laboratory testing capacity for SARS-CoV-2 and an updated national testing strategy , testingManual token issuance to laboratory-confirmed COVID-19 cases became an increasing burden on the contact tracing teams in the health care services as the pandemic grew. From the beginning, we recognized that automatization would have been faster, cheaper, and less demanding on health care professionals. Similar observations have also been made elsewhere . We consWe routinely followed the average timespan or delay from symptom onset until app token use, which seemed to depend on the workload of laboratories and contact tracing teams and increased when case numbers grew. This raised concerns about the usefulness of the app in times when fast notification of potential contacts would have been of most importance and made us revisit automatization of token issuance.Automatic token issuance was pursued as of early 2021 in cooperation with 2 of the largest public health care operators, City of Helsinki and the Helsinki and Uusimaa hospital region, and it was taken into use in June and October 2021 . Tokens The use of the app slowly dwindled over the year 2021 ; the likWith new SARS-CoV-2 variants causing more transmission, several municipalities and hospital regions stopped issuing app tokens in late 2021 to reduce the workload of contact tracing teams. Home tests for SARS-CoV-2 became more common and gradually replaced laboratory testing for much of the population. Positive home test results could not be registered in the app, as tokens were only issued through health care providers. Implementing a self-service option for token issuance was discussed in Finland and elsewhere . AlthougWe designed the Finnish ENA to gracefully retire by creating a screen that thanked the users and informed them about the shutdown . The ENAThe development and launch of the Finnish ENA, Koronavilkku, illustrates how a widely used public health app, requiring new legislation, using new technology, and demanding new ways of cooperation, could be successful within a strict time frame. We consider the cornerstones of this success an excellent team spirit, low level of hierarchy within the project, open communication, avoiding silos, and a clearly defined goal. In addition, it required commitment from the project members and their home organizations.The app was developed with a focus on the end users. Communication and marketing throughout played a key role in ensuring that potential users were familiar with the app, and we believe it contributed to the high number of downloads. Despite this, we received feedback that some health care professionals were disappointed that the app did not provide information to support their contact tracing work. In the literature, mobile apps are considered valuable tools for citizens, health care professionals, and decision makers , but theWe believe that focusing on privacy and data security in communication and implementation strengthened public trust and, in turn, increased app uptake. However, compared to many other countries, public trust in the national government and public institutions is high in Finland . BuildinOnly some countries have published outcomes on their ENAs . The difOther important lessons that we learned along the way include the fact that we did not initially foresee how many updates the app would require as the pandemic and mitigation efforts evolved. Forced updates and feeding text through a dedicated website into the app would have ensured that the guidance to users remained up-to-date, thereby enhancing the potential public health impact of the app. Another lesson learned is how a self-service option or earlier and more comprehensive automatization for token issuing for COVID-19 cases would have eased the burden on contact tracing teams and prolonged the useful lifespan of the app, while also notifying potentially exposed persons quicker and more reliably. Even with lessons learned and reflections on how the app could have been improved, the wide use of the Finnish ENA gave it potential to deliver public health and pandemic mitigation results.