Advanced methods for manufacturing high quality parts should be used to ensure the production of competitive products for the world market. Investment casting (IC) is a process where a wax pattern is used as a sacrificial pattern to manufacture high precision casting of solid metal parts. Rapid casting is in turn, a technique that eases the IC process by combining additive manufacturing (AM) technologies with IC. The use of AM technologies to create patterns for new industrial products is a unique opportunity to develop cost-effective methods for producing investment casting parts in a timely manner. Particularly, stereolithography (SLA) based AM is of interest due to its high dimensional accuracy and the smooth surface quality of the printed parts. From the first appearance of commercially available SLA printers in the market, it took a few decades until desktop SLA printers became available to consumers at a reasonable price. Therefore, the aim of this review paper is to analyze the state-of-the-art and applicability of SLA based 3D printing technology in IC manufacturing, as SLA based AM technologies have been gaining enormous popularity in recent times. Other AM techniques in IC are also reviewed for comparison. Moreover, the SLA process parameters, material properties, and current issues are discussed. For thousands of years metal casting has been recognized as one of the main techniques for producing metal goods. Even today, it remains widely used by the industry. Holtzer et al.  indicateThe process of casting is relatively simple and consists of the following steps: first the metal is melted, and then poured into prepared molds; after metal is solidified and cooled, the mold is destroyed, revealing the casted part. If the part has surface defects, it undergoes further machining to finish the process. Along with other casting methods such as die casting and sand casting, investment casting (IC) is regarded as an indispensable technology for casting metal products that have intricate shapes with high dimensional accuracy and superior surface finish . On the The IC process utilizes a wax pattern to create a ceramic shell that plays the role of the mold. The wax pattern is almost identical to the part that needs to be created considering the thermal shrinkage of the metal. Then, a ceramic slurry is applied on the surface of the pattern to generate the inner walls of the mold. The IC process sequence is shown in Currently there is an increase in the number of AM technological solutions available; this is due to the massive interest in the technology itself, as the availability of these modern technologies and materials make it possible to design, manufacture, and test new parts rapidly. With decreasing cost, consumer grade printers can even be used at home. Additionally, AM technology has affected many areas of human activity such as culture, manufacturing, and even health care, for example. Successful application of AM resulted in making metal implantable devices , parts fWohlers, a consulting agency, in its industry annual worldwide report (2014)  indicateThe interest in using AM for IC industry started shortly after the first AM technology was developed. One of the publications on using SLA for RC was done by Paul F. Jacobs as early as 1992 . In partDuring the design cycle engineers can make changes to the model without compromising manufacturing lead time;Prototypes are useful for verification and assembly design; the case study showed that every fourth design change was due to defects revealed by the prototype model;The assembly of RP models served design optimization that helped to ignore unnecessary engineering change notices. As a result, cycle time can be reduced greatly;Elimination of the cost requalification of casting. As casting is integrated into the first production phase, there is no need to perform mechanical testing of initially casted parts. Therefore, the new approach has less expenditures;Reduction of scrap, due to shortening of machining operation.Five main advantages of using SLA were highlighted:One of the earliest example of when SLA was used for rapid tooling (RT) demonstrated a cost reduction of more than 80%, as reported by Mueller . The SLADespite considerable developments in the 1990s and 2000s, the application of AM did not reach beyond the industrial level at that point of time. It was not until 2012 when the first desktop printers under $5000 arrived on the market, bringing enormous success to the manufacturers. From 2012 onward, AM technology started to reach market shares far beyond industrial businesses. The highly competitive market over the last decade brought tremendous technological innovations to the consumers. Nowadays, desktop 3D printer technology, which meets consumers’ expectations, has become an important part of the AM market. Therefore, it is important to analyze the current state-of-the-art of AM in conjunction with IC. Thus, the aim of this paper is to investigate whether SLA based AM technology is an effective tool for the IC industry. To do so, a comparison of SLA and other AM technologies that are also used in IC will be made. This analysis contains information on process parameters as well as the properties of SLA printed parts and the polymers used. Special attention was given to the dimensional accuracy of SLA printed parts, as it is one of the most important requirements for IC. The last part of the paper discusses current issues and limitations related to SLA applications in IC.Ideally, direct manufacturing of metal parts using AM would be a perfect solution for manufacturers. However, metal AM for most industrial sectors is still at a stage of research and development, with limited industrial applications when compared to the full potential of metal AM. The high cost of machines and consumables, long printing time, and inferior quality of printed parts are some of the factors that hinder the widespread application of metal 3D printing . NeverthThere are different AM technologies other than SLA that have been used in the IC industry ,20,21. TRa), being the major drawback of FDM technology, has been one of the major challenges for the AM industry. It has been found that process parameter optimization can solve the problem partially. For example, layer thickness is the most important parameter to ensure better surface quality, according to Jaisingh et al. [Ra. On the other hand, post-process surface treatments can be utilized to reach desired outcomes. For instance, Jasgurpreed et al. [Ra reached as low as a 27.2 nm value.Fused deposition modeling (FDM) is perhaps the main competitor of SLA in the market. The printing mechanism of FDM is accomplished by the movement of a printer head that heats the thermoplastic filament to reach the melting temperature, and deposits it on the platform in a layer by layer fashion . FDM is h et al. . Howeverd et al.  have sugDuring selective laser sintering, tiny particles of plastic, ceramic, metal, or glass are fused together using heat from a high-power laser to form a solid, three-dimensional object . One of The 3D Printing (3DP) uses a so-called inkjet technology, which is similar to SLS with the difference that instead of sintering the powder with a laser, the powder bed is bounded together by droplets from a print head at specified locations . The proThe Model Maker II (MMII) technique also uses inkjet technology; however, several jets are used. Two inkjets serve different purposes: one for building the pattern, and the other for making wax supports. The supports can be easily removed by applying solvents. What makes the multi-jet method special is the presence of additional machining, which is milling. The milling stage follows each layer to ensure uniform thickness. Although the extra stage greatly increases building time, it helps to generate surface finish with exceptional accuracy. That is why, it has been reported that MMII patterns have better accuracy compared to FDM . Other aLaminated object manufacturing (LOM) employs a completely different technique of AM. During the process a sheet of paper, plastic, or metal covers the printing platform . The nexCAD model generation on any suitable software;STL file generation (3D meshes of triangular elements);SLI file generation (model slicing);Manufacturing layer by layer using SLA printer;Post processing .SLA is an additive manufacturing technology known as vat photopolymerization . The macThe understanding of the effect of process parameters on the parts is essential for successful product design in any manufacturing industry. Although modern 3D printers come with already adjusted “default” process parameters, it is also important to understand the basic working mechanisms of SLA printers. The machine consists of a vat that contains liquid polymer, a platform upon which the object is built, a laser source, and a system of dynamic mirrors for guiding the laser beam. In some recent desktop configurations, the mirror is in a fixed position, and so-called galvanometers act as laser guiding devices, in x and y coordinates. The laser scans the surface of the liquid polymer in a point by point fashion. Once a layer is scanned, the surface needs to be covered with thin film of polymer again for consequent scanning. Here, it is important to understand that the main time consuming process is not the scanning, but the recoating . And thipD is penetration depth at which the beam intensity is reduced to 1/e of its surface value; maxE is the maximum exposure energy on the resin surface; cE is the critical energy required for the transition of the resin from the liquid phase to the solid phase.During printing, the layer thickness is constrained by the wavelength of the laser and its spectral distribution that limit light penetration depths . The curP) within the vat of the stereolithography apparatus, the beam radius (Ow), and the scanning speed (Sv). The relation given in [The maximum exposure energy on the resin surface can be adjusted to control the curing depth, and is a function of laser power (given in  is EquatThe energy at any point within the polymer thickness is given by Equation (3):E at a given position x on the polymer surface is given by Equation (4):As for energy B is the laser spot diameter.The width of polymerized region can be defined as follows  EquationIf the laser spot diameter is of few micrometers, the SLA technology becomes a great tool to manufacture microparts, where layer thickness used decreases down to 1–10 µm . In thatIn 2001 Lee et al.  studied During the building process, the model may have inclined positions, creating challenges in terms of laser beam position. As a result, stair stepping effects emerge . HoweverThe above mentioned defects are initially caused by material imperfections. However, recent advancements in polymer materials science have eliminated many issues to a great extent .To produce high quality castings and ease IC process, it is desired for patterns to possess certain properties, such as high dimensional accuracy; low melting point for effortless burnout; high quality of surface finish; sufficient level of toughness and strength for comfortable handling and finishing; absence of residual ash after burnout; low thermal expansion for avoiding shell cracking. Among AM technologies, SLA is recognized as a highly accurate technique ,56,68. OSome of the pioneer research on the feasibility of using QuickCast for RC was done in 1995 by the European action on rapid prototyping . The proResearch conducted in 2008 by Wu et al.  providesThe dimensional accuracy of a pattern is one of the important requirements in IC, along with its surface roughness. The most suitable approach for assessing the accuracy level of fabricated parts is the evaluation of errors. To evaluate the suitability of the SLA technique, several researchers have investigated the dimensional accuracy of the printed and cast parts. Mathematical, process-related, and material related errors are defined as the primary sources of deviations . One of Rahmati et al.  in 2007 G. Budzik et al.  tested SThe concave and convex surfaces of the turbine blade had an average deviation of 160 µm and 220 µm, for SLA and FDM, respectively.As for the wax pattern, the majority of deviations were within a 500 µm tolerance limit.It was also suggested that SLA is a better option in terms of dimensional accuracy and surface roughness, in comparison to the FDM method for silicon mold making process.Similar research was conducted by Aamir et al.  in 2013,High dimensional accuracy is extremely important in the field of biomedicine and dentistry. Alexey et al. , conductAs can be seen from The dimensional accuracy that SLA technology offers may allow the extension of SLA based IC technology in prosthetic dentistry. The quality of SLA based IC parts was investigated by Ami-Reza et al. in 2019 . The stuDimensional inaccuracy caused by the volumetric change during printing was studied by Islam et al. in 2016 . The resThe variations in dimensions were caused by the photo-polymerization process, according to the authors. The results of the comparison showed a higher dimensional accuracy and repeatability in the z direction for SLA. However, the average datum surface error was greater in SLA, by 68%, compared to PBP. The datum error occurrence was found to be due to the presence of convex curvature produced by the SLA process.Relvas et al. (2012)  performeIn comparison, the best result were obtained for CNC. The next best place was shared between SLA and SLS. The lowest accuracy level belonged to FDM and 3DP. The data in Ra). In many cases the Ra level of objects produced by AM technologies, including SLA, is unacceptable if precise parts are to be manufactured [Ra values of 1.27 - 3.53 µm. The obtained final Ra value depended on the magnitude of the original Ra value of the tested objects and the number of machining runs [Ra value from 17 to 2.1 µm, for the SLA part printed with a manufacturing angle of 10°, according to the study. It was also shown that regardless of the manufacturing angle, coating results in more or less the same Ra value, which is around 2.5 µm.The accuracy of patterns is also highly dependent on surface roughness  light is used as an energy source to initiate photopolymerization . The UV Free radical systems, based on acrylate and methacrylate monomers, were used as common stereolithographic polymeric resins in the infancy stage of SLA. In contrast, modern photopolymers are mainly based on radical and cationic systems .Cationic photopolymerization was developed in the 1970s as an alternative to radical systems . Due to A two-stage curing reaction that consists of gelation and vitrification is used. During gelation, branching of molecules take place, thus increasing the viscosity of the medium. At this stage, the system cannot flow, and two phases coexist: a gel phase and a sol phase. Branching of molecules during gelation is possible only at a particular fractional conversion for each system, depending on the functionality, reactivity, and stoichiometry of the reactive species . As for Monomers and photoinitiators, being the most important components of photopolymers, are not the only constituents of modern compounds. Numerous other additives serve different purposes, among them: flexibilizers, stabilizers, colorants, and many more. As polymer chemistry provides an enormous variety in materials, new compounds with enhanced properties emerge frequently in the market. Recent innovations in the field include new photoinitiators that are water soluble and visible-light-sensitive . RegardiStereolithography technique has not been restricted to using only polymeric material. For instance, there are numerous cases where SLA was employed to build metal and ceramic parts for IC . Photopoparts should undergo debinding and sintering steps after manufacturing;the viscosity of the suspension should be low enough for proper recoating to take place;the suspension should have a sufficient amount of powder to ensure the satisfactory mechanical properties of the product that has gone through rebinding and sintering;the curing depth and resolution must be appropriate; the presence of powder particles interfere in absorption of beam light by the polymer. Thus, the curing depth decreases, leading to an increase of processing time.Bartolo et al.  have lisd50 = 1.5 µm Al powder. Printed parts were sintered and the density of the final parts was reported to achieve 97% of the theoretical value, with flexural strength of 275 MPa. The research group have defined a number of important processing parameters and material properties suitable for successful production of parts that can be readily used in RP and IC. For example, the relation was found between powder concentration, scanning speed, and energy density of the light. According to the authors, an accuracy of ±0.5% could be obtained, provided the process parameters are chosen correctly, and the part has a size of a few centimeters. However, no information was provided regarding surface roughness and overall manufacturing duration.Chartier et al. in 2002  successfThe example of SLA printing of ceramics part was given by Weizhao et al. in 2010 . The priRC of ceramic parts using SLA still remains at laboratory scale. This is due to the low performance of ceramic/metal SLA printed parts in terms of dimensional accuracy, and the overall mechanical properties of both green and sintered parts.One of the significant factors that limits the widespread application of SLA in IC is the issue of ceramic shell cracking. Although the QuickCast platform substantially contributed to solving this problem, IC of small parts with thin sections remains a challenge . MoreoveOne solution for overcoming the problem of shell cracking might be strengthening the ceramic shell ,120,121.Another approach for tackling the issue of ceramic shell cracking is in the area of polymer composition modification . In 1989The majority of research publications on the topic are ten or more years old, thus, new research projects are needed, which might investigate new materials, technologies, and machines currently available.The research is scarce on the application of SLA in indirect tooling.Limited publications are available on the performance of new polymers suitable for IC;An important constraint to the incorporation of RC in foundries is still the high cost of AM machines, building materials, and consumables. Therefore, it is important to search for means of making the manufacturing process more cost effective.The ceramic shell cracking phenomenon remains an issue for parts with thin walls and complicated shapes. Few ways of solving this problem have been proposed by researchers. The two main directions of investigations are materials and process based approaches.Although the dimensional accuracy of SLA printed parts is higher compared to most AM technologies, it is still inferior to conventional CNC machining.Surface roughness is critical in manufacturing precise aerospace and medical products. Therefore, these fields require very low surface roughness values. Like many AM processes, SLA is prone to having a stair stepping effect. Improving the surface quality of SLA printed parts can be achieved through improving process parameters and advancements in materials science. Thus, deep knowledge is required to identify the major parameters that affect the surface roughness.The toxicity level of widely used photopolymers should be studied to evaluate the level of risk and perform a proper life cycle analysis of SLA based IC process.The analysis of recently published articles revealed very few areas that concern SLA application in IC. It can be concluded that the main reason for that is economical. Although the industry is witnessing substantial development of AM technologies, the application of SLA in IC remains economically justified only for small quantity production. The current research trends include topology optimization, improving surface finish, and solving the ceramic shell cracking problem. The study identified probable aspects where further research and development might be needed:The aim of this paper was to review the current status of stereolithography based AM technique in IC manufacturing. Based on the literature review, it can be concluded that there is solid evidence to consider SLA as a great tool for manufacturing both patterns and tooling, which are the main elements of IC industry. Started as rapid prototyping tool in the 1980s, SLA has extended its application area to include rapid IC and beyond. It has been shown that the unique properties of SLA printed parts, like high dimensional accuracy and good surface finish, led to its popularity in the aerospace, automobile, and biomedical industries. With the emergence of desktop printers in the market, a unique opportunity is provided for consumers, small business, entrepreneurship, and academia, who were previously unable to afford the high cost industrial size machines. This paper has also presented basic principles of how SLA works, along with information on photopolymers, which are the raw materials of SLA. The polymer industry, being highly innovative, creates additional incentive for researchers to use new polymers to minimize existing deficiencies involved with currently used materials. One problem that still needs to be overcome is the high thermal expansion of resins that sometimes causes ceramic shell cracking. Economists forecast a substantial growth of investments in additive manufacturing over the next few years. Despite controversial concerns on the sustainability of AM technology, it is believed that AM is likely to revolutionize existing manufacturing trends. This is due to technological progress, and the gradual switching of the market towards customized products. Thus, further investigation and improvements are needed to perfectly incorporate SLA based AM into IC. This is needed for the foundries to properly respond to future market demands .


The COVID-19 pandemic has increasingly disrupted the global delivery of preventive health care services, as a large number of governments have issued state of emergency orders halting service delivery. However, there is limited evidence on the realized effects of the pandemic and associated emergency orders on access to services in low-income country contexts to date. To address this gap, this paper analyzes administrative data on utilization of contraceptive health services by women referred via community health promoters in two large urban and peri-urban areas of Mozambique. We focus on the period immediately surrounding the national state of emergency declaration linked to the COVID-19 pandemic on March 31, 2020. Data reported for 109,129 women served by 132 unique promoters and 192 unique public health facilities is analyzed using logistic regression, interrupted time series analysis and hazard analysis. The results demonstrate that the imposition of the state of emergency is associated with a modest short-term drop in both service provision and utilization, followed by a relatively rapid rebound. We conclude that in this context, the accessibility of reproductive health services was not dramatically reduced during the first phase of the pandemic-related emergency. The onset of the COVID-19 pandemic in March 2020 has disrupted the delivery of both primary and preventive health care services across the globe. This disruption reflects a range of complex factors, but one particularly important cause is the imposition of government restrictions  that limit the provision of health services. In the developing world especially, these pandemic-related shocks may stall recent gains in enhancing access to primary health care, especially for vulnerable women and children .Previous evidence shows similar disruptions in health services during the Ebola outbreak in 2013–2016 generated an additional burden of maternal and child deaths comparable to the direct mortality costs of the Ebola outbreak itself . Though More specifically, in the area of reproductive health care, the COVID-19 shock is projected to cause a substantial diversion of resources . The impMuch of the literature around the effects of COVID-19-linked restrictions remains speculative, however, since many methods of data collection from service users have been suspended due to the risk of disease exposure and transmission. Nearly all national statistic offices surveyed by the UN in May 2020 had at least partially halted face-to-face data collection, and every low-income country respondent reported at least moderate effects from the pandemic on their ability to meet international reporting requirements . As a reOn March 31, 2020, the Mozambican government declared a state of emergency in response to the COVID-19 pandemic. On that day, Mozambique had only eight confirmed cases of COVID-19 but was characterized by the WHO as experiencing local transmission of the virus . In addiThe IFPP program is designed to improve the accessibility of modern contraceptives in three provinces of Mozambique, with the goal of increasing access to contraception for up to 565,000 new users between 2016 and 2021 –14. ThisThe objective of this paper is to analyze the evolution of contraceptive services utilization as accessed through this door-to-door community health worker program in the period immediately surrounding the state of emergency declaration linked to the COVID-19 pandemic in Mozambique. The analysis utilizes real-time administrative data to investigate the effects of the state of emergency on both promoter activity and women’s utilization of facility-based services.Mozambique is characterized by a relatively high fertility rate and low contraceptive prevalence rate, similar to other sub-Saharan African countries. The national total fertility rate was 4.9 children per woman in 2018 compared to an estimated rate of 4.7 children per woman for sub-Saharan Africa overall that year . The mosThis analysis focuses on women beneficiaries of the IFPP program, resident in urban and peri-urban areas of Sofala and Nampula provinces. Levels of education and socioeconomic status in this context are generally low: in Sofala, 26% of urban adults report no education and 43% report primary education, while in Nampula the corresponding figures are 36% and 41% .The IFPP program is centered around services delivered by community-based promoters. Promoters provide counseling around family planning to women in their homes or other community locations. Following the initial session, promoters may meet with beneficiaries up to three additional times over the subsequent months to provide follow-up counseling, depending on the individual woman’s needs  , 21. ProIn any given month, there are typically 100–120 active promoters in the target areas of Nampula and Sofala, and all promoters are women of reproductive age residing in the same community in which they work. Promoters do not supply contraceptive methods directly; rather, they conduct adaptive counseling sessions focused on building relationships and providing credible information on available family planning methods and debunking common myths (i.e. “women who use the pill and injection for many years have difficulty becoming pregnant” or “family planning means not having any children”). At the conclusion of each session, promoters provide women expressing demand for family planning with referrals to public health facilities where services are available at no cost. The data employed is collected by PSI, but only de-identified data excluding any identifying information linked to participants were accessed by the research team. Ethical approval was provided by the Comité Nacional de Bioética para Saúde in Mozambique for the broader evaluation of which this data analysis is a part, and written informed consent was obtained from respondents enrolled in the evaluation. All data are collected via a comprehensive mobile application utilized by promoters and nurses to track activities and referrals. Promoters record the details for each counseling session conducted in the application, including whether a referral was issued. Promoters also capture some basic demographic data about each woman: a categorical variable for age , whether the woman is a current contraceptive user , and whether she reports access to a mobile phone. No other information about demographic characteristics, obstetric or medical history, or knowledge, attitudes, or preferences around contraceptive use or fertility is collected. Data is uploaded to the cloud storage system in real time following the conclusion of the counseling session, and each record is then stamped with the date, time, and GIS coordinates , 23.If the referred woman visits a health facility, this visit is similarly digitally recorded and linked to her referral and the date of her promoter session. These facility records include information about whether the woman received a contraceptive method and are time-stamped. However, program audits and field observations by program supervisors suggest that the timing of when these visits are recorded varies slightly by facility. While many facilities record visits daily and in near real-time, some collect the information and wait to batch-enter records for multiple days at a time, resulting in heaping of the timestamp entries.In total, the analysis includes 109,129 women served by 132 unique promoters and 192 unique public health facilities in Nampula and Sofala over the time period of January 21 to May 20, 2020. Structural programmatic changes  complicate attempts at comparisons with preceding months and years; this analysis therefore focuses on the months immediately before and after the state of emergency declaration on March 31, during which time no other major programmatic changes occurred. In addition, the period in early January was characterized by substantial disruptions linked to the return to work activities post-holidays and the presidential inauguration in Mozambique (held January 15). Accordingly, we begin our analysis on the Tuesday following the inauguration, January 21, to minimize this noise.The analysis focuses on three variables: daily sessions conducted per promoter, the referral rate for promoters, and the contraceptive receipt rate. The first two variables capture promoters’ behavior. They include the daily count of sessions conducted per promoter and the referral rate . These variables enable us to identify whether promoters decreased their activities following the state of emergency declaration, a shift that could reflect promoters’ fear of interacting with members of the public. In addition, promoters may alter their decisions about whether or not to provide referrals to women if they believe that visiting facilities is a risky activity that they should not recommend post-emergency The third variable captures the behavior of women participating in the program; the contraceptive receipt rate is defined as the percentage of referred women who access a prescribed method of contraception at the facility. One important finding is that throughout this period, a facility visit is virtually synonymous with receipt of contraception, as 96% of women who visit a facility receive a contraceptive method. For some analyses, we truncate the sample to focus on women who interacted with a promoter on or before May 6, two weeks prior to the final date observed in the sample, and restrict the variable definition to focus on contraceptive receipt within 14 days. The selection of the 14-day follow-up period is informed by data: in the period prior to the state of emergency, the vast majority of contraceptive receipt following a referral to a clinic is observed to be rapid. Based on women visited by promoters prior to April 1, slightly over half of women who visit a clinic following a referral do so within three days, and 75% do so within two weeks.The objective of analyzing variables linked to both promoters’ behavior  and women’s behavior (contraceptive receipt) is to provide an overview of the effects of the declared state of emergency on both the supply and demand of contraceptive services. Promoters’ behavioral changes are informative about shifts in the supply of services. Behavioral changes observed among women who are visited by promoters are informative about shifts in the demand for services.We provide graphical evidence of trends, simple regression evidence, an interrupted time series analysis and a hazard analysis to analyze whether there has been a decline in service intensity post-emergency. To facilitate interpretation and reduce volatility, graphical trends have been smoothed using a uniformly weighted moving average unless otherwise noted; in addition, the graphs do not include public holidays and weekends, since promoter activity is minimal during non-working days. Smoothing is applied using a seven-day moving window, including the date itself plus three days prior and three days following the date.  The vertical lines on the graphs highlight the first day (April 1) and subsequent extension (April 29) of the national emergency.it), and a binary variable equal to one for contraceptive receipt (Contit) for woman i visited by a promoter on day t. These variables are regressed on a binary variable for post-April 1 (post the state of emergency), Postt,, without adjusting for other individual characteristics. In the second specification, the post variable is interacted with the three individual characteristics reported in the data: a binary variable for whether the user reports access to a phone, a binary variable for whether she currently uses contraception, and a binary variable for age under 25. These characteristics are denoted Xit for concision.The regression analysis is conducted using data at the level of the woman. The dependent variables include a binary variable equal to one for contraceptive referral  Reported access to a phone is a proxy for socioeconomic status as well as access to information. The negative association between the state of emergency and contraceptive receipt is hypothesized to differ based on socioeconomic status; women characterized by higher socioeconomic status and more access to information are hypothesized to show a more limited or null response to the state of emergency. Similarly, we expect a differential response to the state of emergency for women who are current users (who have a demonstrated demand for contraception), and women over the age of 25 . In both cases, the hypothesis is that women with these characteristics will not respond to the state of emergency.All specifications are estimated using logistic regressions clustering standard errors at the level of the week; estimation is conducted in Stata version 14. All regressions are estimated both using the full set of data available (1/21-5/20) and for a restricted time period encompassing the six weeks immediately surrounding the state of emergency (3/1-4/15). The latter restricted sample allows for the identification of the short-term effects of the declaration of the state of emergency.The interrupted time series analysis is conducted using the same data and examining the variables contraceptive referral and contraceptive receipt. These variables are regressed on a continuous time variable ; a binary variable for Post-April 1; and the interaction of Post-April 1 and the time trend. The binary variable captures the shift in the intercept post-April 1, and the interaction captures the shift in the trend in the post period. The regression is estimated employing ordinary least squares and including as additional covariates the three demographic variables described above , and fixed effects for province, promoter and neighborhood. Standard errors are clustered at the level of the week.Finally, we estimate a Cox proportional hazards model in order to estimate the effect of the state of emergency (again captured as a binary variable for Post-April 1) on the probability of contraceptive receipt, controlling for a continuous time variable. For this analysis, the sample is not truncated and includes all women reported to receive facility referrals through May 20, the final day observed in the data. This model allows for censoring of data that arises given that some women have not yet visited a health facility at the close of the study. We present the estimated hazard ratios and standard errors, again clustered at the level of the week.We begin by characterizing the sample of women observed in the data. 16% of women are below age 20; 32% are between age 20 and 24; 28% are between age 25 and 29; 21% are between age 30 and 39; and only 4% are over age 40. 62% of women report that they are already using contraceptives as of their first interaction with the promoter, and 27% report they have some access to a mobile phone.Figs In contrast to the pattern observed for promoter activity overall, While promoters demonstrated little change in behavior in response to the state of emergency, female participants in the program responded more robustly, as shown in The regressions employing contraceptive referral as an outcome variable are reported in Columns (1) through (3). The only significant results are observed in Column (2), where both the estimated coefficient for Post-April 1  and the estimated interaction term with current user  are statistically significant. Examining the predicted probabilities, the probability of referral for a woman who is not a current user of contraception in fact increases in the post period, while the probability of referral for a woman who is a current user declines. The regressions employing contraceptive receipt are reported in Columns (4) through (6), and the only significant results are observed in Column (4), where both the estimated coefficient for Post-April 1  and the estimated interaction term with reported phone access  are statistically significant. Again, examining the predicted probabilities, the probability of receipt for a woman who does not report phone access declines in the post period, while the probability of receipt for a woman who reports phone access increases.To provide a more nuanced depiction of shifts in trends in the pre and post emergency period, Finally, we report a Cox proportional hazards model to estimate the effect of the Post-April 1 state of emergency on contraceptive receipt. The estimated hazard ratio associated with the binary variable for Post-April 1 is .941 , suggesting a reduction in the probability of contraceptive receipt in the Post-April 1 period. The estimated hazard ratio associated with the days elapsed variable is 1.002 .This analysis suggests that in general, the effect of the COVID-19 related state of emergency on utilization of contraceptive services in the context of a health promoter program providing door-to-door referrals to public health facilities in urban Mozambique has been modest in the first two months of the emergency. This finding is similar to previous evidence of a minor shift in contraceptive use in response to the Zika outbreak in Brazil , with thIn interpreting the shifts in promoter behavior, the brief reduction in the number of sessions per promoter observed in Despite this short-term shift, however, our analysis suggests that promoters continued to refer women to health clinics to access contraceptive methods and more formal counseling from nurses; in an interrupted time series analysis, there is evidence of a downward shift in the estimated intercept for the referral rate following April 1, but a positive shift in the trend. This is suggestive evidence that promoters’ family planning messaging was not eclipsed by the pandemic messaging. Rather, these patterns may support the potential for future synergies via the utilization of existing community health workers to disseminate critical public health information in conjunction with previously established work activities .In addition, we observe that women who visit facilities almost uniformly take up contraception, both before and during the state of emergency. In theory, a state of emergency could affect the availability of contraceptive methods themselves at clinics as well as staff to provide methods. However, there is no evidence of such an effect in this context.Our analysis of women’s responses also suggests that there is a short-term decrease in the contraceptive receipt rate. Given that the majority of women receiving contraceptives through the IFPP program are utilizing short-term methods , a decline in the receipt rate could have meaningful implications.Importantly, the observed disruptions to both service provision and contraceptive receipt appear to be largely short-term, and the rebound is rapid. This may reflect two important points. First, the state of emergency was not as stringent in Mozambique as in other countries, and there were no limitations on local freedom of movement or clinic closures. Second, the short-term growth of COVID-19 cases in Mozambique was relatively slow. As of the final day observed in this analysis , only 146 cases and zero deaths were reported nationwide [At the same time, there is some evidence that the decline in contraceptive referrals and receipts is not uniform for all women in the post-emergency period. In contrast to our ex ante hypotheses, the predicted probability of contraceptive referral in fact increases for women who are not current users of contraception post-emergency, and the predicted probability of contraceptive receipt increases for women who report access to phones. These seemingly counterintuitive patterns may reflect behavioral responses to the state of emergency. On the side of promoters, promoters may perceive that facility visits are more risky or inconvenient during the emergency period, and thus may shift their referrals toward women they perceive to be at higher risk of unintended pregnancy–women who are not using contraception at all–increasing the probability of referral for this subgroup.On the side of women receiving services, we can hypothesize that women who have access to phones have more information about the COVID-19 pandemic and the anticipated health or economic risks, and increase their demand for contraception. Women who do not have access to phones do not show any comparable effect. Similarly, women who were previously non-users of contraceptives may also have shifted their fertility intentions during the state of emergency and thus received more referrals, though we do not have any direct measurement of fertility intentions. Our findings of differential patterns for women who do not report access to mobile phones echo the caution provided in Greenleaf et al. 2018 that reliance on cell-phone based interventions may be risky given their potentially limited reach in some contexts . In regiThis analysis has a number of limitations, and among the most important is the limited data available. While using administrative data has notable advantages, including rapid access to the data and access to the full sample of program participants, one key disadvantage is that only very minimal data is collected. In particular, no data is available on women’s health history, sociodemographic characteristics, and preferences around fertility. Accordingly, we are unable to adjust the empirical analysis for these important covariates.Additional limitations include that the analysis focuses on only prescribed contraception provided in public health facilities in a specific setting (two urban and peri-urban regions of Mozambique), and focuses on one particular model of service delivery via community health promoters and public clinics. Promoters in the IFPP program are also specifically incentivized to encourage women to visit clinics for contraceptive services, and thus may have continued to provide such encouragement and support during the state of emergency; this pattern may not be observed in other contexts.Moreover, the state of emergency in Mozambique was not as stringent as those imposed in other settings, and the effects of stricter states of emergency may have been different. Accordingly, these findings are not necessarily generalizable for the provision of contraceptive or reproductive health services in other contexts, or for the provision of other forms of preventive health services.Overall, our findings suggest that the adverse effects of a state of emergency linked to COVID-19 on the delivery of contraceptive services via a community-based health promoter program were modest and short-term. In this context of urban Mozambique, a door-to-door method of service delivery for reproductive health services does not seem particularly vulnerable to the introduction of a state of emergency. There is, however, evidence of heterogeneous effects across women, including differential effects for women who have access to cell phones.This evidence is informative about a particular service provision model for a particular population, but has clear limits in its relevance vis-a-vis other forms of reproductive health and preventive health services provided in other contexts. Given the uncertain duration of pandemic disruptions, it remains important to identify resilient models of service delivery that can also reach relatively more vulnerable populations.


Participants declaring constipation compared with other participants were characterized by higher proanthocyanidins intake  and intake per 1000 kcal . Similar association for constipation was observed in the case of energy value of diet and protein intake, but only for proanthocyanidins intake, it was confirmed in the logistic regression model . The positive influence of habitual dietary intake of proanthocyanidins was confirmed in the studied group of patients with ulcerative colitis in remission, as this intake may have increased the production of mucus, which is beneficial for intestinal healing, and may have reduced the frequency of bowel movements. However, further experimental human studies are necessary to confirm the potential influence of proanthocyanidins intake in patients with ulcerative colitis in remission.A number of bioactive components of diet are indicated as potential dietary factors for the management of ulcerative colitis, while the recent study conducted in an animal model revealed that proanthocyanidins from grape seeds exert a broadly positive impact. The aim of the study was to verify the influence of dietary proanthocyanidins intake on the symptoms of ulcerative colitis in remission in human subjects. The study was conducted in a group of 55 participants  in remission of ulcerative colitis confirmed based on both the Mayo Scoring system and Rachmilewitz index. Their habitual dietary intake of proanthocyanidins and intake recalculated per 1000 kcal of diet was assessed and it was verified whether they are associated with symptoms of ulcerative colitis. The energy value of diet and intake of other nutrients were analyzed as potential interfering factors. Participants declaring the presence of mucus in their stool compared with other participants were characterized by higher proanthocyanidins intake (142 vs. 75 mg;  Ulcerative colitis is classified as one of the inflammatory bowel diseases, defined as a chronic inflammatory condition resulting in diffuse friability and superficial erosions of the colonic wall, associated with bleeding . AlternaProper nutrition is one of the most important issues that should be addressed in patients with ulcerative colitis . This isMany bioactive components of diet are indicated as potential dietary factors for the management of ulcerative colitis, and these components are even thought to be possible alternative therapeutic agents in the future . These bFlavonoid compounds are one of the potentially beneficial components that may influence the course of ulcerative colitis. Flavonoids are plant-derived hydroxylated polyphenolic molecules that are characterized mainly by antioxidant activity, together with some anti-inflammatory, antiviral, anticancer, and neuroprotective activities through different mechanisms of action . One subConsidering the potential positive influence of proanthocyanidins for treating ulcerative colitis, based on animal model studies, the present study aimed to verify the influence of dietary proanthocyanidins intake on the symptoms of ulcerative colitis in remission in human subjects.The presented study was conducted in cooperation between the Dietetic Outpatient Clinic of the Institute of Human Nutrition Sciences, Warsaw University of Life Sciences (WULS-SGGW) with three gastroenterology outpatient clinics that consult patients with ulcerative colitis: (1) the Gastroenterology Outpatient Clinic of the Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, (2) the Gastroenterology Outpatient Clinic of the Central Clinical Hospital of the Ministry of Interior in Warsaw, and (3) the Gastroenterology Outpatient Clinic of the Public Central Teaching Hospital in Warsaw.The study was conducted based on the approvals of following ethical committees: (1) Bioethical Commission of the Central Clinical Hospital of the Ministry of Interior in Warsaw (No. 35/2009), and (2) Bioethical Commission of the National Food and Nutrition Institute (No. 1604/2009). It was conducted according to the guidelines laid down in the Declaration of Helsinki, while participants provided their written informed consent to participate in the study.The study participants were ulcerative colitis patients with confirmed remission from the following gastroenterology outpatient clinics: (1) the Gastroenterology Outpatient Clinic of the Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, (2) the Gastroenterology Outpatient Clinic of the Central Clinical Hospital of the Ministry of Interior in Warsaw, and (3) the Gastroenterology Outpatient Clinic of the Public Central Teaching Hospital in Warsaw.-Being Caucasian;-Being aged 18–80 years;-Being nonhospitalized for any disease;-Endoscopically diagnosed ulcerative colitis confirmed in the clinic records;-Having confirmed remission of ulcerative colitis—endoscopic remission: image without any changes or disappearance of vascular network, erythema, inflammatory polyps allowed; clinical remission: assessed based on the Mayo Scoring System ; and the Rachmilewitz index  for the assessment of the ulcerative colitis activity , as desc-Having been in clinical remission for at least six weeks;-Having had constant drugs doses for at least six weeks confirmed by patientThey were recruited by their gastroenterologists, based on the following inclusion criteria:-Pregnancy;-Diagnosed cancer;-Any gastrointestinal resection.And the following exclusion criteria:Based on the indicated inclusion and exclusion criteria, the total number of 55 participants were recruited, while 19 males and 36 females volunteered to participate in the study. The characteristics of the studied group were presented in the previous publications, while the majority of respondents declared no more than three bowel movements per day in the period of remission , and theThe study included the analysis of diet, as well as the analysis of the disease symptoms in the period of remission. The previous analysis verified the association between dietary intake of carotenoids ,20, as wThe assessment of disease symptoms was based on the self-reported data, that were obtained from the respondents. They were asked about the following issues: abdominal pain, presence of blood, mucus and pus in their stool, constipations, flatulence, tenesmus, and daily number of bowel movements. In spite of the fact that all included patients were in confirmed remission, the applied criteria of the Mayo Scoring system and the Rachmilewitz index allowed the presented symptoms to be observed . MoreoveFor the daily number of bowel movements, participants were asked about their typical number of bowel movements per day, on the typical day during their remission. They were asked to not focus only on the present day, or present week, but to declare the typical number for their general remissions.For the abdominal pain, presence of blood, mucus and pus in their stool, constipations, flatulence, and tenesmus, participants were asked about each symptom separately, if they declared it during their remissions, while using the structured questionnaire. Before asking any question, participants were instructed that they should base their declarations only on their own feelings and observations, not on any suggestion, or supposition that they should have any symptoms, or on the results of their medical examinations. Patients did not have to describe precisely the intensity of their symptoms , or amount , but they were only asked if such a symptom is for them present. The included symptoms of ulcerative colitis were based on the Qualitative Focus Group Study by Waljee et al. , as theyAt the beginning patients were asked about specific symptoms—if they require to have a description of them presented and, if required, an image of them was verbally described. Afterwards, they were asked about their symptoms before the ulcerative colitis diagnosis and then, about the current symptoms .Finally, they were asked to summarize their observations, while specifying if the intensity or frequency of a symptom is during their remissions higher than it was previously (when they did not have ulcerative colitis). Based on the obtained data, participants were for each symptom divided into two subgroups: respondents declaring the symptom , and respondents not declaring the symptom .The habitual intake was assessed with no specific dietary intervention conducted. The dietary intake was assessed based on the three-day dietary records that were conducted by the participants during three typical, random, but not consecutive days, two of them being week days and one a weekend day . ParticiParticipants were asked for scrupulous recording of the products consumed and for not changing their typical dietary habits, due to recording. Afterwards, each participant had to describe orally the consumed dishes, while the dietitian asked additional questions, if it was necessary to specify any information. While describing the food, respondents were shown photographs of food products and dishes in a Polish atlas of food products’ serving sizes, to verify the serving sizes, and all participants had their three-day dietary records verified by the same dietitian, to reduce bias.1, B2, B6, B12, folate, niacin, C. The Dietetyk 2.0, the Polish dietitian software with the nutritional value database [In order to assess the proanthocyanidins intake, the United States Department of Agriculture (USDA) Database for Proanthocyanidins Content of Selected Foods  was appldatabase , was appp > 0.05, U Mann–Whitney test).The applied treatment was taken into account as a potential interfering factor for the association between dietary intake and symptoms, so it was verified whether the applied treatment is associated with the proanthocyanidins intake. Patients were divided into groups stratified by: number of groups of applied medications for the groups of 5-aminosalicylic acid, corticosteroid and immunosuppressive medications (1 group/2 groups/3 groups), 5-aminosalicylic acid (applied/not applied), corticosteroid (applied/not applied), and immunosuppressive medications (applied/not applied). The conducted statistical analysis revealed that there is no such association . Finally, in the third stage, in the cases when not only proanthocyanidins intake was stated to be associated with symptoms, but it was also observed for the other nutrients, the logistic regression was applied. Additionally, for daily number of bowel movements, the Spearman rank correlation coefficient was used to verify correlations.The distribution was verified using the Shapiro–Wilk test. Afterwards, three-stage statistical analysis was conducted. Due to nonparametric distribution, in the first stage, the Mann–Whitney U test was applied to compare sub-groups characterized by various symptoms, for the proanthocyanidins intake. In the second stage it was applied to compare sub-groups for the energy intake and intake of other nutrients that may have interfered the observed association  and PQStat software 1.6.6. .The level of p = 0.4431) and intake recalculated per 1000 kcal of diet (p = 0.4040). As no difference of proanthocyanidins intake between patients with and with no abdominal pain was observed, the other stages of the statistical analysis were not conducted.The comparison of proanthocyanidins intake between patients with and with no abdominal pain is presented in p = 0.4021) and intake recalculated per 1000 kcal of diet (p = 0.1451). As no difference of proanthocyanidins intake between patients with and with no presence of blood in stool was observed, the other stages of the statistical analysis were not conducted.The comparison of proanthocyanidins intake between patients with and with no presence of blood in stool is presented in p = 0.0441) and intake per 1000 kcal . As there was a difference of proanthocyanidins intake between patients with and with no presence of mucus in stool, the other stages of the statistical analysis were conducted. The identical comparisons between patients with and with no presence of mucus in stool were conducted for energy value of diet and all possible interfering nutrients , but for none of them the difference of intake between patients with and with no presence of mucus in stool was stated .The comparison of proanthocyanidins intake between patients with and with no presence of mucus in stool is presented in p = 0.2010) and intake recalculated per 1000 kcal of diet (p = 0.2284). As no difference of proanthocyanidins intake between patients with and with no presence of pus in stool was observed, the other stages of the statistical analysis were not conducted.The comparison of proanthocyanidins intake between patients with and with no presence of pus in stool is presented in p = 0.0289) and intake per 1000 kcal . As there was a difference of proanthocyanidins intake between patients with and with no constipations, the other stages of the statistical analysis were conducted. The identical comparisons between patients with and with no constipations were conducted for energy value of diet and all possible interfering nutrients . The statistically significant differences were stated for energy value of diet  and protein intake recalculated as grams per kg of body mass , as the higher energy value of diet and the higher protein intake were stated for participants not declaring constipations  than those who declared .The comparison of proanthocyanidins intake between patients with and with no constipations is presented in p = 0.0183; OR = 1.01; 95% CI 1.00–1.02).For all the nutritional factors that were stated to be associated with constipations incidence , the logistic regression was conducted. It was revealed, that in the logistic regression model, while three indicated variables were taken into account, only daily proanthocyanidins intake remained a factor significantly associated with constipations incidence (p = 0.8200) and intake recalculated per 1000 kcal of diet (p = 0.8399). As no difference of proanthocyanidins intake between patients with and with no flatulence was observed, the other stages of the statistical analysis were not conducted.The comparison of proanthocyanidins intake between patients with and with no flatulence is presented in p = 0.3568) and intake recalculated per 1000 kcal of diet (p = 0.3811). As no difference of proanthocyanidins intake between patients with and with no tenesmus was observed, the other stages of the statistical analysis were not conducted.The comparison of proanthocyanidins intake between patients with and with no tenesmus is presented in p = 0.5597; R = –0.0804) and intake recalculated per 1000 kcal of diet .The analysis of correlation between proanthocyanidins intake and daily number of bowel movements is presented in Although a positive influence of proanthocyanidins from grape seeds on the course of ulcerative colitis in a rat model has been observed , the mecA previous study by Li et al.  showed tStreptococcus mutans adhesion); stomach (inhibition of Helicobacter pylori adhesion as well as its urease and Vacuolating cytotoxin A (VacA), antiemetic properties, slowing of gastric emptying, modulation of HCl and mucus secretion, and ulcer healing); small intestine ; and colon .While summarizing the effect of proanthocyanidins on the gastrointestinal tract, Cires et al.  stated tTaking into account the observed results, it is crucial to properly interpret the effects of proanthocyanidins for colonic mucus and bowel movement frequency, as higher proanthocyanidins intake was noted for participants showing presence of mucus in stool and those with constipations.Proanthocyanidins have the ability to stimulate mucus synthesis and secretion . They alIn spite of the fact that there are also factors other than ulcerative colitis that may influence mucus observed in stool, in a group of patients with confirmed disease, it may be above all interpreted as associated with this disease. Based on animal model studies, it may be also hypothesized that the improper mucosal intestinal layer may contribute to colitis development . At the The pathway described above, associated with the ability of proanthocyanidins to stimulate mucus synthesis and secretion, may explain the results observed in the presented study, as individuals with the presence of mucus in stool showed a twice-higher intake of proanthocyanidins than other individuals. As the mechanism of the effect of proanthocyanidins, Iwasaki et al.  proposedCroton spp. or Calophyllum spp.  as a “Method of treating secretory diarrhea with enteric formulations of proanthocyanidins polymer” by Rozhon et al. [It is also indicated that proanthocyanidins may prevent or even revert diarrhea by decreasing fluid accumulation and reducing watery stools . This pan et al. .On the basis of the results noted for the studied group, it could be considered that proanthocyanidins may have a beneficial effect on patients with ulcerative colitis. The antiulcer activity of mucus  may reduIn spite of the fact that the observations from the conducted study are interesting and may be promising, the limitations of the study must be also listed. The most important issue is associated with the fact that the studied group was homogenous , but as a result, it was relatively small. Moreover, in spite of the fact that numerous nutritional factors were taken into account, there may be also other potential food components that may influence the disease, such as other phenolic compounds, and other bioactive compounds. At the same time, also factors other than diet-related, e.g., associated with any concurrent diseases, age, or body mass may have influenced the observed symptoms. Last, but not least, the most reliable studies would be those assessing the effect of administration of a known amount and concentration of proanthocyanidins, or grape seed extract containing proanthocyanidins, in the controlled clinical trial. Such studies should be conducted in order to verify the observations from the presented analysis. However, it must be emphasized that it would be a model of supplementation, not of a dietary intake, as presented in presented study.The positive influence of habitual dietary intake of proanthocyanidins was observed in the analysis conducted for the studied group of patients with ulcerative colitis in remission, so it may be supposed for such patients and should be verified in further studies. In the studied group, intake of proanthocyanidins may have increased the production of mucus, which may be beneficial for intestinal healing, and may have reduced the frequency of bowel movements. However, further experimental human studies are necessary to confirm the potential influence of proanthocyanidins intake in patients with ulcerative colitis in remission.


Buildings account for a majority of the primary energy consumption of the human society, therefore, analyses of building energy consumption monitoring data are of significance to the discovery of anomalous energy usage patterns, saving of building utility expenditures, and contribution to the greater environmental protection effort. This paper presents a unified framework for the automatic extraction and integration of building energy consumption data from heterogeneous building management systems, along with building static data from building information models to serve analysis applications. This paper also proposes a diagnosis framework based on density-based clustering and artificial neural network regression using the integrated data to identify anomalous energy usages. The framework and the methods have been implemented and validated from data collected from a multitude of large-scale public buildings across China. ObviousAcademia has devoted much effort to solving this problem recently, as some researchers have proposed the utilization of semantic web technology to enhance the interaction between BIM models and physical data ,10,11. TIn this research, a unified framework for the extraction and integration of BIM models and building energy consumption monitoring data has been proposed. A hierarchical data model for building energy consumption monitoring data has been established in the framework, and an integration method for raw monitoring data has been proposed by deducing conversion logic from static topological information, allowing for the standardization, and thus integration, among otherwise isolated data. On this basis, energy usage anomaly diagnosis methods have been devised using integrated static and dynamic data, which employs density-based clustering and artificial neural network regression.The remaining part of this paper is organized as follows. This paper presents the design of a unified framework for the extraction and integration of static building information, and dynamic building energy consumption monitoring data, as well as statistical learning methods based on the framework to diagnose energy usage anomalies. This section provides a review of researches related to the topic in literature.The primary sources of dynamic building energy consumption monitoring data are sensors and smart meters installed inside buildings. These devices usually collect data on a fixed time interval that are either direct utility consumption readings, such as power or water usage, or data that reflect the operational status of the building, including indoor environmental parameters such as room temperature, humidity, light intensity, etc. and operational parameters of Mechanical, Electrical, and Plumbing (MEP) equipment, e.g., the cooling water temperature of the air conditioning system, etc. These sensors and meters are usually managed by BEMSes, which monitor the energy usage status of buildings throughout the operation and maintenance phase in buildings’ lifecycles, and are sometimes embedded with simple strategies to adjust energy usage through actuators based on sensor and meter input . HoweverBIM models are carriers of static building information and digital representations of the physical and functional characteristics of buildings and attached facilities . The uniIn summary, lack of interoperability among BEMSes is a prominent problem in building energy consumption management on the scale of building groups or manifolds, with comprehensive data models for building energy consumption data covering multiple granularities also scarce. The involution of BIM models in energy management were also mainly for visualization purposes, and the building contextual information has not been sufficiently utilized. This paper presents a framework for the extraction and integration of building energy consumption monitoring data and BIM data by establishing a hierarchical building energy consumption data model, and proposing the corresponding data construction method from raw readings of sensors by conversion logic deduction from BIM models. Thus, existing BEMSes could be incorporated into the framework by satisfying relevant requirements on sensors and BIM models.Anomaly detection refers to the process of detecting abnormal events not conforming to expected patterns . AnomaliAlmost all techniques of statistical learning, both supervised and unsupervised, have been employed in building energy consumption diagnostics, as well as ensemble learning methods, employing multiple learning algorithms simultaneously ,44. NumeThis paper proposes a unified framework for the automatic extraction and integration of building energy consumption monitoring data, as well as BIM models, as illustrated in The model is constituted of four layers. The data sources layer contains sources for data in the framework, including sensors and smart meters for dynamic data, and extended BIM models for static data. The data extraction layer retrieves relevant data from the sources. For dynamic data, raw readings of the sensors and smart meters are extracted, which are stream monitoring data sampled by the sensors and meters at regular intervals. Existing BEMSes are also possible sources for dynamic data, through an Extensible Markup Language (XML) protocol proposed in this research. For static data, metadata for the sensors, as well as the building topology need to be extracted. conversion rules from raw readings to integrated data are deduced by topological Boolean operations in the Data integration layer, which performs the integration on the retrieved raw data following the deduced rules to convert raw sensing data into integrated data conforming to the data model. Finally, the data storage layer stores the integrated in both relational and NoSQL databases, and serves data to succeeding analyzing applications. The cornerstone of building energy consumption data analytics tasks, and all data analytics tasks in general, is to ascertain the data model, i.e., the inclusion and exclusion criteria of data, and their organization and description thereof. In this research, a generic hierarchical data model is proposed, whose hierarchy is illustrated in The data model is organized as a four-tier tree hierarchy, each containing a number of utility consumption items corresponding to different granularities. The top tier contains three items corresponding the whole building granularity, i.e., the overall power, water, and gas consumption of the entire building. The top-middle tier contains the overall consumption of heating and cooling energy of the building, whose granularity is classified intermediate as the heating and cooling system implementation differ across buildings. For example, buildings in northern China usually have access to centralized heating in winter, where heating energy consumption is metered independently from power consumption, while buildings in southern china usually use air conditioning for heating purposes in winter, in which case heating energy consumption is essentially part of the overall electric power consumption. Organizing the heating and cooling energy of buildings into an intermediate level ensures compatibility with buildings of different heating and cooling system implementations. The bottom-middle tier corresponds to energy consumption records of building subsystems, including lighting, air conditioning, elevators, fans, etc. Lastly, the bottom tier contains records of the finest granularity—energy consumption of specific facilities. Each item contains 4 attributes, as shown in In the implementation of the framework, each energy item of each building would be assigned a code that uniquely identifies their combination, which is what the itemcode attribute stores. The time and value attributes are trivially designed to store the time and value of the energy consumption monitoring record. Finally, the unit attribute is of a simple type system specifically designed to represent the units of the records, as shown in The type system is composed of three entities forming a single inheritance line. The base entity, unit, is an interface entity representing the type system containing a dimension array under the SI system , and is inherited by the SIUnit entity, representing units that are decimal exponents under the SI system, such as joule, ton, cubic meter, etc. The SIUnit entity is in turn inherited by the ConversionUnit entity, representing units that are not convertible by decimal exponents under the SI system, such as kilowatt-hour, the most commonly used metric for power consumption. The inheritance chain ensures the Unit attribute, whose apparent type is the Unit base entity, could be bound to the correct underlying entity through the dynamic binding mechanism of Object-Oriented Programming (OOP). In this way, the proposed data model is complete and capable of representing energy consumption data across multiple buildings and granularities. The design of the data model, in general, is straightforward. As has been noted previously, multiple data models for the representation of building energy data have been proposed and implemented before, yet this data model has the advantage of the capacity for multi-building and multi-granularity representation, and therefore more suitable for data integration purposes. The design of the data model is in part based on the ontological building energy consumption data representation by Zhang et al.  ImplemenThe unified data model provided a criterion for data inclusion for further analysis, and a standardized way to organize and describe them. However, in the data sources side resides substantial heterogeneity, as numerous classification schemes and data models have been implemented by the existing BEMSes. In contrast, there exists the IFC standard as a universally accepted neutral standard for BIM models. To extract valid data for the generation of standardized data conforming to the data model, this research identifies and proposes compulsory static data requirements. Extraction techniques are then discussed, including an XML protocol devised for exporting data from existing BEMSes.Standardized classification of sensors and smart meters is a prerequisite for the extraction of valid dynamic data, such that the same physical quantity is encoded identically across buildings. On this basis, sensor and meter metadata in BIM models could be standardized. Besides the classification code of the physical quantity measured by the sensor, another attribute the entities for sensors and meters are obliged to possess is the facility or subspace whose energy consumption is being measured. Together with other necessary information, such as the name, identifier, and data transmission protocol, sensors could be embedded in BIM models through the extensibility mechanism of IFC. Such extended BIM models constitute the data requirements for buildings to be incorporated into the framework. With the proliferation of BIM technology applications, this requirement would be satiable by more and more buildings in the future. Large quantities of tools and APIs readily exist for extracting BIM and IFC data, which could be used to extract the sensor metadata and building topologies, to be used in the data integration layer.Data extraction for the dynamic part would be more straightforward, as sensor and meter readings could be collected through their respective data transmission protocol. Common IoT protocols include ZigBee, MQTT, Bluetooth, and Wi-Fi etc., which all have readily available data extraction tools. To utilize data in existing BEMSes, this research also proposed an XML interface for exporting BEMS data, as shown graphically in The XML interface, as shown in It has been one of the rising concerns in recent years that identifying information of citizens has been surreptitiously solicited and abused with the advent of data collection practices, thus violating privacy rights. In this research, the designs of the data model and the data collection procedures from the sensors included lists of physical quantities to be collected, among which only energy and resource consumption information of buildings and MEP systems are included. This information, though possibly could be used for building occupancy deduction, contains no indications for the identities of occupants.The last remaining task in the framework is to convert and integrate raw readings extracted from the sensors and smart meters or BEMSes to data conforming to the universal data model described in The goal of the method is to deduce a formula for the generation of each energy item in the data model, e.g., the generation formula of the overall electric power consumption of a specific building. Therefore, the spatial entity corresponding to the item is first identified in the topology tree of the building, which was extracted from the BIM model. For example, the spatial entity corresponding to the overall power consumption of the building is the topological entity representing the entirety of the building. Then, spatial entities of all sensors in the building that monitor the relevant physical quantity are identified in the topological tree. In the case of electric power consumption, all meters and sensors monitoring positive active electric energy are involved. The final step is to generate a Boolean operation formula that takes sensor spatial entities and yields the target entity, using valid Boolean operations , which could be trivially converted to a formula of the readings of the sensors. Thus, formulae for the conversion are deducted, and hence the framework completes.An abundance of information is deposited in building energy consumption data, and extraction of such knowledge through appropriate analysis methods prove invaluable to optimizing building energy consumption management decisions. The identification of anomalies in building energy usage, or building diagnostics, is one of the most important and most researched applications building energy consumption data analytics. Since anomalies are the data points that do not conform to an expected pattern or behavior, anomaly detection tasks are essentially the learning of the underlying patterns of building energy consumption.Unsupervised learning refers to the learning methods on data with unknown ground truth. Among unsupervised learning methods, clustering has been most frequently employed for anomaly detection tasks, with most researchers performing k-means clustering on building historical energy consumption data. K-means clustering requires as input the number of clusters to group the input data into, and groups data points into clusters of hyperspheres in the metric space. However, the number of clusters is hard to estimate beforehand, and the data points produced by the same energy usage pattern are not always hyper-spherical in the metric space. Therefore, an unsupervised learning approach using density-based clustering is proposed in this research, to eliminate explicit anomalies in the monitoring data.Unlike unsupervised learning, supervised learning methods are trained on labeled data, and ANN is one of the most powerful and popular models for supervised learning. ANN is capable of regressing non-linear and high-order patterns among the input and output, is most often used to make predictions in building energy consumption data analytics. Authentic data are then compared against forward predictions for diagnostics, where data points whose deviation from the prediction exceeds a threshold are considered anomalous. Building static data, or building context, logically, are relevant to building energy consumption, yet have never been the subject of regressions against energy consumption data in the researches, since previous researches have all been performed on the level of single buildings or lower, where static data are invariant. On the basis of the framework described in Explicit anomalies are anomalies caused by errors in the facilities or sensing devices, are usually apparent to building managers. For example, negative reading of electric energy consumption would be classified as explicit. Clustering methods are more advantageous in identifying explicit anomalies than supervised learning methods as they are devoid of the problem of overfitting. This research proposes a density-based clustering algorithm to identify explicit anomalies in building energy consumption data, which includes the following 4 steps. The flowchart of the algorithm is as shown in (1)Input GenerationSince the goal of this algorithm is to identify and eliminate explicit anomalies, it suffices to perform the analyses within buildings instead of across buildings. This method performs clustering over two-dimensional data, with cross-sectional historical data of the same energy item from the same time of day of the same building as one dimension, and temperature as the other, since it is the most significant meteorological factor affecting energy usage. Temperature records are available from local meteorological agencies.(2)Data StandardizationDensity-based clustering algorithms require as input a distance metric among data points, as well as a threshold for points to be considered neighbors. To diffuse the difference in the unit measurements of the two dimensions, data standardization is performed on the input, to convert both dimensions into standard normal distributions.(3)Parameterization and ClusteringIt suffices to use Euclidean distance as the distance measurement since it is conservative. Another parameter to designate is the minimum number of points for a neighborhood to be considered cluster, denoted as m or minPts, usually one more than the number of clusters. The final and most vital parameter is the distance threshold for two points to be considered neighbors, known as the epsilon. In this research, the epsilon is determined using the knee locator. To identify the knee locator, first the distance to the mth closest point for each point has to be found and stored in an array. Then, the array is sorted indexed in ascending order. Finally, the point with the maximum curvature is found, and the distance thereof is taken as the epsilon. The last step in this part is to perform Density-Based Spatial Clustering of Applications with Noise (DBSCAN)  clusteriImplicit anomalies refer to anomalies that are the result of changing energy usage patterns, which are usually not visually extruding. ANN is a powerful statistical learning method that potentially learns non-linear and high-order patterns in the input data, yet with known weaknesses in the tendency of overfitting. With explicit anomalies eliminated by the clustering algorithm described in The network model in this algorithm is a conventional multi-layered backpropagation neural network. It has three layers: an input layer, a hidden layer, and an output layer. The input layer includes a number of neurons representing a series of input parameters, divided into four groups. The first group represents the static building information, and comprises here of three parameters: building area, building orientation, and building function. The building area is valued as the total building area measured in square meters, and building orientation is denoted by the number of degrees it takes to rotate from due north to the direction the façade of the building is facing clockwise. The building function is represented using a dummy variable corresponding to an enumeration of building functionality. The second group contains meteorological data, and here includes the temperature in Celsius degrees and relative humidity in percentage points. Then, a number of historical energy consumption data immediately preceding the time to be estimated are organized in the third group, known as the historical data. Finally, the day of week, numbered 1–7, and hour of day, numbered 0–23, constitute the fourth group, the temporal data. The output layer has a single neuron for the dependent variable, i.e., the energy consumption to be estimated. The hidden layer has a number of neurons depending serving as relays between the input and output. Weights in the connections are generated at random from a gaussian distribution at initiation, and adjusted based on the error feedback once the training starts using Levenberg–Marquart backpropagation algorithm.Since explicit anomalies have been eliminated previously by the clustering algorithm, overfitting should be expected at a minimum level. The logistic sigmoid function is used as the activation function in each neuron.To validate the extraction and integration methods, the universal data model, the framework has been implemented as part of an energy consumption management system construction effort. A total of 234 large public buildings from 11 cities across China have been incorporated into the framework after satisfying the metadata requirements, and a NoSQL database based on Hadoop has been deployed on the cloud end to store collected data. The sensors and meters in these buildings have been surveyed and tabulated following the data requirements described in To date, the framework has been running for almost two years, covering a total building area of more than 12 million square meters. The sensors and smart meters collect information mostly every 5 min, and the raw data are integrated to be conforming to the data model with a time interval of 1 h. To date, more than 100 million integrated records have been accumulated in the storage, serving as valuable resources for not only diagnostics but numerous data analytics applications. The density-based clustering algorithm has been validated using data from the Xinzhuang Comprehensive Building, a large-scale public building located in Xuhui district, Shanghai, China. The building measures 22 m in height, with seven floors aboveground, and one floor underground, totaling an area of 9992 square meters. The input data for the algorithm are two-dimensional data comprised of outdoor dry-bulb temperature readings retrieved from local meteorological agencies, and the overall air conditioning subsystem power consumption of the building. Data at 15:00 each weekday from February to October 2020 are used. The data are then standardized so that both dimensions are converted to follow standard normal distributions. Euclidean distance is used as the distance metric for the standardized data points, while the minimum number of points for a neighborhood to be considered a cluster, m, is chosen to be 3, one more than the dimensionality. The epsilon is located using the knee locater, as described in To validate the implicit anomaly detection method using artificial neural network regression with integrated static data, data from 10 large-scale public buildings in Shanghai are used to supply variability for static building information. There are shopping malls, office buildings, hotels, and hospitals among the 10 buildings, whose building function attributes are assigned the dummy values of 1–4 respectively. The overall power consumption data of the 10 buildings from November 2019 to October 2020 are used, with an interval of 1 h after integration . Contemporary meteorological data are retrieved from local meteorological agencies, including dry-bulb temperature, and relative humidity. Temporal data that represents the day of week and hour of day are also generated. Six distinct Sliding window sizes between 4 and 24 have been used, and the number of hidden neurons varied between 10 and 100. The dataset was randomly divided into a training set and a testing set by a ratio of 9:1, and the training continues until improvement of loss is less than a preset tolerance of 0.0004. The prediction result is evaluated using Rooted Mean Squared Error (RMSE). Since the algorithm diagnoses anomalies through forwarding predictions, it follows that more accurate predictions on authentic data indicate better diagnostic performances. The influence of the number of hidden neurons and the length of the sliding window is shown in Each line in To test the validity of introducing static data in the input, a comparison experiment was performed. Two models were trained independently, with identical model parameter settings as described in the paragraph above. The same data are used as in the previous experiment, and the same train–test split was applied to the input of both models. The only distinction between the models is that one model has to build static data in the input, while the other does not. 2, of the regression on the left is greater than that on the right, indicating that additional energy consumption variations are explained by the static data.In For the validation of the framework, the extraction and integration methods, and the diagnostics algorithms proposed in this research, an implementation of the system was presented in the case study, with more than 200 buildings accessed for data. The diagnostics algorithms have also been experimented, using data extracted and integrated into the framework. The achievement has supported the effectiveness and feasibility of the data extraction and integration methods. The experiment result of the explicit anomaly detection algorithm using density-based clustering also proved successful, as the visually explicit anomalies have been correctly identified and eliminated. Also, since the clusters in the result are of arbitrary shape, the performance of k-means clustering under the same circumstance could be put into question. Finally, the experiment result of the implicit anomaly detection method using ANN regression proved that the introduction of static data is of value, and improves the prediction result by a moderate margin. This, retrospectively, proves the value of the unified data extraction and integration framework, which made regression on the scale of building multitude possible.This research, inevitably, is not devoid of vulnerabilities. The authors have identified the following problems that need further improvements.(1)The feasibility of the extraction and integration methods depends on the quality of static metadata. Though BIM has been increasingly universal in the Architecture, Engineering, and Construction (AEC) industry, its application in building Operation and Maintenance (O&M) management is far from ubiquitous. Even under circumstances where the BIM model is present, the inclusion of the stipulated metadata in the model is not guaranteed, and costs extra time and labor to complement.(2)Although the anomalies identified in the clustering experiment are visually explicit, there lacks a proper quantitative measurement for the clustering result. Intra-cluster similarity, in this case, is not well-defined, and an appropriate indicator remains to be worked out.(3)The performance of the ANN could potentially be improved by normalizing input data, especially static building data, to accelerate convergence and prevent local optima stagnations. However, the normalization of input could be canceled out by linear transformations of weights in the process of training, thus theoretically input normalization does not affect training output. Due to the simplicity of the network employed in this research, the authors have also not found statistically significant improvements to the prediction accuracy by the introduction of input normalization. It is nonetheless noteworthy that in more complex networks, this could be overturned.(4)The results of the ANN regression experiment, although demonstrated the effectiveness of the introduction of static data in the diagnostics, also manifested its magnitude of improvement is only moderate. The improvement in the prediction results cannot be guaranteed to justify the extra cost of implementing the framework. However, some more relevant static data were not available to the authors for the experiment, such as exterior transparency, insulation thickness or the coefficient of heat transfer of the walls, it is possible that further introduction of these variables would continuously enhance the prediction results. Moreover, from an absolute perspective, the error reported in this research is higher than in similar works than applied neural networks in time-series predictions. Despite the differences in data quality, network design and complexity, and input selection, this also signals the potential to further enhance prediction performances ,49,50,51Much research has been conducted on building energy consumption data, and sensing data in general, extraction and integration, and many practical BEMSes are implemented and installed in buildings. However, interoperability among heterogeneous BEMSes remains a problem, and a universal data exchange method for integrating energy consumption monitoring data from different buildings remains absent. Numerous studies have also been done on the diagnostics of building energy usage, with researches employing ANN particularly abundant. Yet, the problem of overfitting in supervised learning has not been overcome due to data noises, and building static data have never been considered for the lack of integrated dynamic and static data.In this research, a framework for the automatic extraction and integration of building energy consumption monitoring data is proposed, containing a unified hierarchical data model for the description of building energy items covering different granularities, and corresponding data extraction techniques involving an XML protocol for exchanging data with BEMSes, and data integration techniques by conversion formulae deduction from topological data and metadata. On this basis, a density-based clustering algorithm along with the parameterization method was proposed to identify and eliminate explicit anomalies, to improve data quality for the succeeding regression. Then, an ANN regression method with building static data in the input is proposed to identify implicitly anomalous energy usage patterns. The methods and algorithms have been validated and tested in experiments, proving the value of the framework, and the effectiveness of the diagnostics methods.For future research, the utilization of ensemble learning in the diagnostics combined with static input is a possible direction for further studying. Appropriate indicators for the clustering algorithm and further incorporation of more relevant static attributes are also worthy topics. Hardware implementations of the network would also be within consideration, should the performance of the methods improve further.