Labor Hours Research Articles

A small boat for fish feeding

This study focuses on development of a solar-powered Arduino Mega-driven robotic boat designed for efficient fish feeding in aquaculture. By integrating IoT technology and a mobile app, the project aims to reduce labor costs and improve feeding practices while addressing challenges associated with manual feeding, which previously failed to adequately cover the entire pond area. The research specifically centers on Nile tilapia production. Experimental results show that the robot emulates manual feeding with an average response time of 1.82 s for feeding initiation and 2.17 s for movement initiation. It efficiently distributes feed across a 4000 m² area in 9 min, outperforming the manual method, which takes 32 min. Fish fed by robotic boat exhibit an 18.71 % weight gain compared to those fed by hand. The robotic boat farm consumes a total of 11.480 kg of feed to produce 7.6 kg, while the hand-fed farm required 16.185 kg of feed to produce 6.5 kg. This results in feed conversion ratios of 1.51 and 2.49, respectively. The study finds an overall cost reduction of 46.13 % due to decreased labor hours. We strongly recommend adopting this robotic boat for optimizing tilapia feeding in earthen ponds.

Individual choice and objective demand in a Classical framework

AbstractTaking a cue from some passages of The Wealth of Nations, this paper defines notions of maximum willingness to pay and of individual surplus expressed in hours of labour for a two‐good pre‐capitalist economy. From the individual surplus, a consistent objective theory of individual choice is constructed, and a demand schedule free from subjective elements is derived.

Strain-Based elevation monitoring during construction of the Salesforce Tower

Anticipated complexities associated with monitoring elevation changes during construction of the 326 m tall Salesforce Tower in San Francisco prompted the implementation of a strain-based system. This system utilizes strain gages embedded into the tower’s reinforced concrete walls and the resulting measurements are inputs into one of three shortening estimation models of varying complexity and applicability. This methodology was successfully utilized to monitor time dependent shortening due to axial, shrinkage, and creep strains in the tower. Strain-gage based systems assist with slender tower construction in urban areas because the tower’s slenderness coupled with adjacent obstacles stretch the limits of traditional or alternative instrument capabilities and they provide redundancy of measurement to ensure accuracy. This paper is a case study of how a strain-based elevation monitoring system helped this project to be successful. The most relevant findings are: 1) the shortening estimation models were in agreement with conventional survey measurements (±4.6 mm) within their recommended tower height and temperature range capabilities; 2) implementation of this system resulted in a net monitoring cost reduction on the order of 15 %, 400 less labor hours, and reduced potential for project delays; and 3) improvements are needed for supplying power to the sensors as there were interruptions, cut cables, and lack of sources that led to a 44 % sensor success rate. Given the need for structural health monitoring, the successful outcomes documented in this paper, and the potential for continued improvement by way of, for example, wireless and battery free sensing technologies, the work documented herein is believed to be an incremental advancement to the state-of-the-art of tall buildings.

Husbands' wages and married women's labor supply in urban China

In this study, we examine the impact of husbands' wages on married women's labor force participation (extensive margin) and hours worked (intensive margin) in urban China from 1995 to 2018. We emphasize that changes in a husband's wages alter each spouse's relative contribution to the household, thus highlighting the important role of gender identity norms in the association between husbands' wages and married women's labor supply. We find that a 1% increase in husbands' wages is associated with a 0.018 percentage point decrease in married women's labor force participation and a decrease of 1.45 h worked annually. When gender identity norms are controlled, these numbers increase to 0.024 and 1.94, respectively. Additionally, we observe significant heterogeneous effects for wives of different ages and education levels and with varying numbers of children. The negative association between husbands' wages and women's hours worked has become stronger over time.

Machine learning prediction of structural dynamic responses using graph neural networks

Prediction of structural responses is essential for the analysis of structural behaviour subjected to dynamic loads. Existing approaches are limited in different ways. Experimental tests are expensive due to the requirement of intensive labour hours and specialised equipment. Numerical models can provide high-fidelity and labour-effective simulation of impact tests after proper validation, but it comes with high computational costs, which prohibit the usage of numerical methods for intensive and large-scale simulations in a design office. Data-driven machine learning approaches are also applied to structural response predictions, but they often exploit direct input–output mapping schemes that predict static field variables without capturing the dynamic response process. To close these gaps, we propose a novel machine learning approach based on graph neural networks (GNN) for full-field structural dynamics prediction. Our approach adopts a discretised representation of structures with an iterative rollout prediction scheme, and therefore it can simulate comprehensive spatiotemporal structural dynamics, providing the full potential for structural dynamics analysis. With several benchmark tests, it is demonstrated that our approach can generate accurate predictions of related field variables, e.g., displacement, strain, and stress, for different structures with a wide range of input parameters, such as structure geometry, impact speed and location. Additional interpolation and extrapolation tests are also conducted to show that our approach enjoys inherent generalisability and can produce satisfactory prediction even when all inputs are sampled outside of the training distribution. Our approach is also efficient and runs an order of magnitude faster than the commonly used numerical competitors. As the first attempt of using GNN for structural dynamics prediction and the result is promising, it is believed that GNN is well-suited for effective and efficient prediction of dynamic structural responses.

Abstract PO-010: Operationalizing the health care system electronic medical record to create head and neck cancer research and screening databases

Abstract Introduction: A “living” prospective database for tracking patient outcomes and creating clinical trial screening populations would be useful for head and neck multidisciplinary teams and can be translated to innumerable populations of interest. The database should be rapidly accessible, economical, accurate, and transcend the typical 5-year length of grants. We hypothesized we could construct such a database and piloted the concept using patients within our head and neck cancer active surveillance population. This population consists of patients at high risk for the development of primary and secondary oral carcinoma over 20 years. A second goal was identifying subjects for oral leukoplakia studies and construction of genomic atlases. Methods: Through the University of Minnesota Clinical and Translational Sciences Institute (CTSI), we performed an IRB interrogation of our patient population in the EPIC electronic medical record (EMR) of 4,496 unique patients seen by the senior author and identified 1,375 unique deidentified patient records representing individuals with likely preneoplastic lesions. Our approach included 30 International Classification of Disease (ICD) 9 and 10 codes corresponding to 120 unique mucosal head and neck precancerous lesion descriptors. Information included typical demographic and risk data, laboratory, pathology, and possible staging data. All curated data were stored on CTSI servers with direct access to data analysis software. Results: The ICD 9 and 10 codes queried encompass 36 low risk, 16 moderate/low risk, 8 moderate/high risk, and 55 high risk lesion codes. 25/30 of the queried ICD 9 and 10 codes (>12,000 instances) were identified in the 4,496 patients queried, encompassing 1,375 unique patients, with most patients harboring multiple ICD codes. We identified 464 patients with diagnosed high risk lesions, 346 with moderate/high risk lesions, 692 with moderate/low risk lesions, and 728 with low-risk lesions. Several research functions in the EMR were identified to construct screening lists. From IRB approval to obtaining the data set from the CTSI, this process requires fewer than 24 hours of combined labor, minimal cost, and did not require manual chart abstraction. Conclusions: From our preliminary success in curating a dataset of patients diagnosed with high-risk oral lesions, we conclude that utilization of ICD 9 and 10 codes as inclusion criteria represents an efficient and simple way for busy practitioners to screen large amounts of clinical data for study populations of interest (>1 × 106 EMR). We will develop quality assurance and improvement measures to audit data accuracy. Further expansion of this work will apply similar algorithmic dataset curation to medical records acquired from clinicians beyond the current study population. Critically, this process could be used for a variety of conditions to develop comprehensive longitudinal databases to examine both retrospective and prospective outcomes, provided an ICD 9 or 10 code exists for the condition and coding is accurate and consistent. Citation Format: Lindsey Mortensen, Alexander J. Dwyer, Beverly R. Wuertz, Frank G. Ondrey. Operationalizing the health care system electronic medical record to create head and neck cancer research and screening databases [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-010.

The Joint Commission’s Ongoing Professional Practice Evaluation Process: Costly, Ineffective, and Potentially Harmful to Safety Culture

ObjectiveTo evaluate the estimated labor costs and effectiveness of Ongoing Professional Practice Evaluation (OPPE) processes at identifying outlier performers in a large sample of providers across multiple health care systems and to extrapolate costs and effectiveness nationally. MethodsSix hospital systems partnered to evaluate their labor expenses related to conducting OPPE. Estimates for mean labor hours and wages were created for the following: data analysts, medical staff office professionals, department physician leaders, and administrative assistants. The total number of outlier performers who were identified by OPPE metrics alone and that resulted in lack of renewal, limitation, or revoking of hospital privileges during the past annual OPPE cycle (2022) was recorded. National costs of OPPE were extrapolated. Literature review of the effect of OPPE on safety culture in radiology was performed. ResultsThe evaluated systems had 12,854 privileged providers evaluated by OPPE. The total estimated annual recurring labor cost per provider was $50.20. Zero of 12,854 providers evaluated were identified as outlier performers solely through the OPPE process. The total estimated annual recurring cost of administering OPPE nationally was $78.54 million. In radiology over the past 15 years, the use of error rates based on score-based peer review as an OPPE metric has been perceived as punitive and had an adverse effect on safety culture. ConclusionOPPE is expensive to administer, inefficient at identifying outlier performers, diverts human resources away from potentially more effective improvement work, and has been associated with an adverse impact on safety culture in radiology.

Capacity planning with limited information

Limited information about the demand for some of the resources needed to produce goods and services (e.g., incomplete and imperfect bills of materials) forces firms to use heuristics when planning resource capacity. We examine the performance of five heuristics: two drawn from practice, two that modify observed approaches, and one motivated by theory. We measure performance as the ratio of the expected cost of supply–demand mismatch from using a heuristic to the value in the full‐information solution. Numerical analysis shows that a simple heuristic that is common in practice—plan rigorously for a few “driver” resources with high‐quality information and use ratios (e.g., 0.25 indirect labor hours per machine hour) to project the capacities for the remaining “non‐driver” resources—is robust and efficient. Using more than one driver resource to plan for the same non‐driver resource delivers significant gains. Reducing measurement error with respect to the consumption of driver resources dominates the gain from reducing errors in other aspects. Indeed, with high measurement error, collecting information that reduces other sources of error could decrease overall performance. Finally, a greedy algorithm of choosing the most expensive resources as drivers is optimal.

Evaluation as Devaluation: The Labour of Critique in Fashion Education

A “critique” means something quite different in the art and design classroom than it does in the seminar room: an event of assessing students’ artwork. The monopolization of critique as a labour of appraisal serves to enforce that the hours fashion students spend crafting wearable garments are not remunerable labour hours but intangible investments in their own professional and personal development, installing a quite literal distinction between the material work created by the student and the immaterial work of the tutor to assign, guide, and grade it. This pedagogy helps naturalize the asymmetrical distribution of time and obligation through which the arts university precaritizes faculty in short-term work contracts while imprisoning students in long-term loans. By licensing its monopoly on critique to instructors within the studio-classroom so they may evaluate and thereby devaluate the work of students, the university insulates itself from solidarity between its different constituencies.

Increased efficiency could lessen the need for more staff in companion animal practice.

To evaluate technical efficiency of US companion animal practices. 60 independently owned companion animal practices selected from the 2022 AVMA Veterinary Practice Owners Survey. A ratio of the weighted sum of outputs to weighted sum of inputs was computed for each practice (ie, decision-making unit [DMU]). Inputs included labor (hours worked) and capital (fixed costs and number of exam rooms). Outputs (or production) included annual gross revenue, number of patients seen per year, and number of appointment slots per full-time-equivalent (FTE) veterinarian per year. Data envelopment analysis was used to optimize the ratio and estimate relative efficiency (RE) scores. 25 (42%) practices were classified as having high efficiency (RE = 1 or 100% efficient), 26 (43%) as having moderate efficiency (RE > 0.7 but < 1.0), and 9 (15%) as having low efficiency (RE ≤ 0.7). Mean RE scores for moderate- and low-efficiency practices were 0.83 and 0.66, meaning they could have reached their current production levels with 17% or 34% less resources. Per the model, if all 60 practices were 100% efficient on the RE scale, 22 fewer FTE veterinarians, 47 fewer FTE veterinary technicians and assistants, and 43 fewer FTE nonmedical staff would be needed overall. These preliminary findings suggested that efforts to optimize efficiency could allow companion animal practices to meet demands for their services without necessarily needing to hire more staff. Such efforts might include engaging support staff to their full potential and implementing automated processes. Additional research is needed to identify routines or workflows that distinguish high-efficiency practices from others.

Reorganization of inventory to improve kitting efficiency and maximize space utilization

In industry 4.0 Smart factories, assembly time and space utilization are improved by supplying pre-sorted kits and optimal arrangement of storage tubs. However, the process of kitting itself in its current state at the place of this research is inefficient. With kitting around the entire research facility, improvements had to be made in several areas including but not limited to excess travel, retrieval time, and redundant inventory updates, to simplify the process flow and alleviate the burden on pickers. The current state of kitting consumes a large number of labor hours resulting in excess strain and fatigue due to the picker's long travel distances for retrieving the parts and creating an ergonomic hazard with huge weights pushed on kit carts. This paper investigates the gaps in the current kitting process by identifying the root causes using Process Failure Modes Effects Analysis (PFMEA) while also optimizing kitting space. This research established an optimized kitting process for 21 parent parts based on commonality, standardization, and frequency of co-occurrence of parts. This led to a reduction in kitting times by 36% to 49% for high demand parts and improved space utilization by 30% to 36%. The approach used in this paper is simplistic and generic in the form to render itself applicable to different kitting processes in small to medium shop companies and is of practical importance.© 2023 Society of Manufacturing Engineers (SME). Published by Elsevier Ltd. All rights reserved.This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under responsibility of the Scientific Committee of the NAMRI/SME.

The Interplay of Migrant Workers’ Working Hours, Income, and Well-Being in China

There is a history of overwork in China, and regulations to protect workers are insufficient. This study explores the relationship between working long hours and self-rated health among rural-urban migrant workers in China. Survey data from the 2018 China Family Panel Studies (CFPS) is used to construct a simultaneous equation model, and the 3SLS method is applied. The results showed that: (1) Migrant workers had good health. However, overtime work is very common among migrant workers in China, and male migrants work more overtime. (2) Migrant laborers’ health and income are causally related, with better health leading to higher income. In contrast, the compensatory effect of income by extending working hours on health is smaller than the damage caused by overtime work for the male migrants who have more severe overtime work, resulting in a negative income effect on health. (3) The incentive effect of income on labor supply and the positive interaction effect of increasing labor hours to increase income are only reflected in the standard labor time sample. Therefore, for the heavy overwork group whose working hours have already reached the limit, income increases can no longer motivate them to extend their labor hours. Therefore, provincial and national policy transformations are needed to regularize working hours and remuneration while maintaining individual health.

A hybrid model based on convolution neural network and long short-term memory for qualitative assessment of permeable and porous concrete

Estimating design factors like concrete strength and durability is complicated by the cement industry's practice of producing multiple grades of cement for different uses, necessitating substantial labor hours and monetary investment. The experimental findings of accelerated carbonation-induced corrosion and associated durability characteristics of concrete built with high-volume Class F Fly Ash (FA), including AC impendence, half-cell potential, water permeability, and volume of permeable voids. FA was added to ordinary portland cement at varied replacement amounts (0–70%) to create concrete specimens. The concrete specimen has been prepared by varying different proportions of water cement ratio (0.45, 0.40, and 0.35). To predict the compressive strength and carbonation level of concrete, this study presents a simulation environment based on Artificial Intelligence (AI) that makes use of input parameters such as water/cement ratio, fly-ash percentage, and time duration. Here, One-Dimensional Convolution Neural Network based Long Short-Term Memory (1D-CNN-LSTM) has been proposed for estimating the carbonation depth and compressive strength of concrete. The developed model will be compared with other state-of-the-art techniques, including DL and ML-based techniques. The obtained R2 values from the proposed 1D-CNN-LSTM regression network deliver accuracy of 80% for estimating carbonation depth and 96% for predicting compressive strength. The proposed methodology demonstrates the use of modern AI-based techniques in the actual design model and illustrates the development of DL methods such as LSTM and CNN.

Pregnant Prisoners in Shackles

Pregnant Prisoners in Shackles

Aryl-diazonium salts offer a rapid and cost-efficient method to functionalize plastic microfluidic devices for increased immunoaffinity capture.

Microfluidic devices have been used for decades to isolate cells, viruses, and proteins using on-chip immunoaffinity capture using biotinylated antibodies, proteins, or aptamers. To accomplish this, the inner surface is modified to present binding moieties for the desired analyte. While this approach has been successful in research settings, it is challenging to scale many surface modification strategies. Traditional polydimethylsiloxane (PDMS) devices can be effectively functionalized using silane-based methods; however, it requires high labor hours, cleanroom equipment, and hazardous chemicals. Manufacture of microfluidic devices using plastics, including cyclic olefin copolymer (COC), allows chips to be mass produced, but most functionalization methods used with PDMS are not compatible with plastic. Here we demonstrate how to deposit biotin onto the surface of a plastic microfluidic chips using aryl-diazonium. This method chemically bonds biotin to the surface, allowing for the addition of streptavidin nanoparticles to the surface. Nanoparticles increase the surface area of the chip and allow for proper capture moiety orientation. Our process is faster, can be performed outside of a fume hood, is very cost-effective using readily available laboratory equipment, and demonstrates higher rates of capture. Additionally, our method allows for more rapid and scalable production of devices, including for diagnostic testing.

Assessment of the impact of climate and non-climatic parameters on cocoa production: a contextual analysis for Cameroon

Agriculture remains the mainstay of Cameroon's economy, with cocoa as one of its key export commodities. However, cocoa production may be affected by climate-related stressors. This study assesses the influence of climate and non-climate parameters on cocoa performance in Cameroon. We use time series data for temperature, rainfall, carbon dioxide emission, land use, labour hours, pesticide application, and cocoa output in Cameroon spanning 60 years (1961 to 2021). Trend analyses reveal a stochastic response of crop production under climate variation. Leveraging on the perennial crop supply response framework, a Vector Error Correction Model (VECM) reveals short-term climate impacts on cocoa production. The econometric estimation shows that climate and non-climate parameters explain the variations in cocoa output. More specifically, the short-run results reveal that temperature, carbon dioxide emission, land use, and pesticide quantity significantly increase crop yield, whereas rainfall decreases it substantially. Furthermore, the long-run analysis indicates that temperature, rainfall, carbon dioxide emission, and land use are significant negative determinants of the yearly changes in cocoa output. We recommend government policy reforms which address access to land, subsidies/climate finance and improved production technologies to reduce greenhouse gas emissions and enhance farmers' adaptive capacities to climatic stressors.

Preparing surfaces for shredding: Skateboarding, repair, and care across scales

AbstractIn cities around the world, skateboarders repair surfaces and objects for the purposes of play using techniques to fill, smooth, and fabricate. Research in social and cultural geography focuses on the ways citizens repair and care for material objects using do‐it‐yourself (DIY) practices. Despite continuities, repair work by skateboarders does not strive to improve neglected, absent, or dysfunctional infrastructure for the common good, as in cases from literature on DIY urbanism, nor to subvert objects, texts, and surfaces to make political statements, as in cases from literature on tactical urbanism. Skateboarders do repair and care work to prepare surfaces for playful damage benefitting other skaters and onlookers enjoying the spectacle. By exploring these widespread but under‐researched acts of repair and care and the circuits of knowledge that reproduce them, this paper makes four arguments. First, skateboarders do repair and care work to generate ‘spots’ for skateboarding from assemblages of objects and surfaces intended for other purposes. Transforming spots brings otherwise mundane patches of the city to life through thousands of tiny acts of repair and care. Second, repair and care work by skateboarders is most effective when barely visible to people outside the culture. However, repaired surfaces make their way to large audiences, often millions of viewers, through skateboard photography and video, giving some of them an outsized life across time and space. Third, knowledge about techniques of repair and care are considered an important part of skate culture to be learned and shared. Protocols of care shape acceptable degrees of modification to surfaces and objects, and as skateboarding globalises so too do these protocols. Fourth, acts of repair and care have no guarantees of longevity. Hours of labour can be destroyed by direct acts to stop skateboarding and by indirect acts emanating from dynamics of urban change.

Evidence of the Unintended Labor Scheduling Implications of the Minimum Wage

Problem definition: The effect of the minimum wage is an important yet controversial topic that has received attention for decades. Our study is the first to take an operational lens and empirically study the impact of the minimum wage on firms’ scheduling practices. Methodology/results: Using a highly granular data set from a chain of fashion retail stores, we estimate that a $1 increase in the minimum wage, although having a negligible impact on the total labor hours used by the stores, leads to a 27.7% increase in the number of workers scheduled per week, but a 19.4% reduction in weekly hours per worker. For an average store in California, these changes translate into four extra workers and five fewer hours per worker per week. Such scheduling adjustment not only reduces the total wage compensation per worker but also reduces workers’ eligibility for benefits. We also show that the minimum wage increase reduces the consistency of weekly and daily schedules for workers. For example, the absolute (relative) deviation in weekly hours worked by each worker increases by up to 32.9% (6.6%) and by up to 9.7% (2.1%) in daily hours, as the minimum wage increases by $1. Managerial implications: Our study empirically identifies and highlights a new operational mechanism through which increasing the minimum wage may negatively impact worker welfare. Our further analysis suggests that the combination of the reduced hours, lower eligibility for benefits, and less consistent schedules (that resulted from the minimum wage increase) may substantially hurt worker welfare, even when the overall employment at the stores stay unchanged. By better understanding the intrinsic tradeoff of firms’ scheduling decisions, policy makers can better design minimum wage policies that will truly benefit workers. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1212 .

Implementation Preparation Costs of Virtual Interview Training in Pre-Employment Transition Services: A Budget Impact Analysis.

Virtual Reality Job Interview Training (VR-JIT) and Virtual Interview Training for Transition Age Youth (VIT-TAY) demonstrated initial effectiveness at increasing employment among transition-age youth with disabilities engaged in pre-employment transition services. We characterized activities and estimated the labor and non-labor costs required to prepare schools to implement VR-JIT or VIT-TAY. Implementation preparation and support teams reported labor hours throughout the implementation preparation process. Implementation preparation labor hours at 43 schools cost approximately $1,427 per school, while non-labor costs were $100 per trainee (student). We estimated the replication of implementation preparation labor activities would cost $1,024 per school (range: $841-$1,208). Most costs were spent in delivery planning and teacher training. Given that implementation preparation costs can be barriers to intervention adoption, our results provide critical information for contemplating future implementation of VR-JIT or VIT-TAY.

On the properties of the labour wedge: hours worked and government transfers in perspective

ABSTRACT Questions surrounding the labour wedge and the tax wedge in the United States are complicated by the fact that, historically, there is a lack of coherent relationship between the series of hours worked (based on standard measurements) and that of the tax wedge. This has been cited as grounds for discounting the tax wedge as a viable explanation for the behaviour of the labour wedge. In this paper, I explore an alternative measurement of labour hours in the United States in a bid to clear up some of the morass surrounding the tax wedge and hours worked. In the process, I show that, the labour wedge is rather more aligned with available labour hours over the business cycle than it does actual hours worked. Moreover, cyclical properties of the available hours series, however puzzling, are explained by the presence of a government transfer scheme which I introduce in the household side of the market. Also, the presence of the transfer scheme alters the marginal rate of substitution (MRS) between consumption and leisure, and by doing so, reverses the cyclical properties of the tax wedge. This puts the tax wedge in alignment with the labour wedge over the business cycle.