Average Cycle Research Articles

Patterns of self-reported diarrhea in patients with cancer receiving chemotherapy.

Diarrhea is prevalent in individuals with cancer undergoing chemotherapy and negatively affects their outcomes, treatment adherence, and survival. With the majority of patients receiving chemotherapy in an outpatient setting, treatment-related toxicities, including diarrhea, are experienced while at home, and, therefore, their prevalence, frequency, and associated distress remain largely uncaptured. This study aimed to assess the prevalence and severity of patient-reported diarrhea and the relationship between diarrhea severity and its associated distress. We performed a secondary analysis of diarrhea severity and associated distress ratings (1-10) reported over the course of chemotherapy by individuals with various types and stages of malignancies. Symptoms were assessed daily through an automated telephone system. Out of 345 participants, 217 (62.90%) reported at least one episode of diarrhea. Of the reported diarrhea occurrences, 60.39% were classified as mild (1-3), 34.62% as moderate (4-7), and 4.99% as severe (8-10). The mean duration of mild, moderate, and severe diarrhea was 3.57, 4.84, and 1.43days, respectively. Of all diarrhea episodes, 97.40% were reported between cycles 1 and 8, with cycle 1 having the greatest number of reported episodes. Out of these, cycle 5 had the highest average diarrhea severity (4.02) and cycle 8 the lowest (2.98). The average number of diarrhea reports per patient was 4.94 for participants in mild symptom group, 3.98 in moderate, and 1.78 in severe. A simple linear regression revealed a significant beta of 0.91 (p < 0.001) between diarrhea severity and the associated distress score. Diarrhea affected over 60% of study participants. Its severity was highly correlated with patient-reported distress. Clinicians need to be aware that diarrhea can significantly disrupt patients' wellbeing and make it a priority of patient education and post-treatment assessment.

The Overlooked Role of Roadworks in Micromobility’s Accessibility

Transforming cities often comes with the overlooked consequence of roadworks. Complex underground infrastructure, such as cabling, anti-flooding systems, and heating works, makes urban transformations costly and time-consuming. This trend will likely persist, making it important to understand its impact on our daily lives. For the first time, we present a comprehensive dataset on construction work in Copenhagen and analyse travel time delays in cycling trips by expanding a cycling speed model based on extensive trajectory data. Our findings reveal that construction activities can reduce average cycling speeds by 0.4 to 1 km/h on affected segments, significantly affecting mobility.

Gynaecological Health Patterns and Motherhood Experiences of Female Professional Football Players

The aim of this paper is to explore the gynaecological health patterns, contraceptive use, body perception, and motherhood experiences of female professional football players. The participants were recruited via email using FIFPRO (Football Players Worldwide). Online questionnaires were completed by consenting participants. The mean age at menarche was 13.5 years with an average cycle length of 26 days, and a bleeding period of 5 days. Cycle irregularities were experienced by 30%, and menstrual symptoms by 74%. Half of the participants used contraceptives, 60% using hormonal contraceptives, primarily oral contraceptive pills (38%), followed by implants (20%). The body satisfaction score was normal but there was a high drive-for-thinness (DT) score. The motherhood rate was low (1%), with participants experiencing normal conception, vaginal delivery, return to training after 6 weeks, and return to competition after 12 weeks. Our findings are consistent with findings in other elite female athletes with cycle irregularities and a significant number of cycle-related symptoms. The majority of those using contraceptives preferred hormonal contraceptives, reflecting trends seen in other elite athletes. While body satisfaction scores were normal, there was a high DT score, similar to that observed in lean and weight-category sports. The motherhood rate was low, consistent with previous findings in professional football players and other elite athletes. This may be due to a lack of financial support during pregnancy and the post-partum period. FIFPRO and its affiliated unions are negotiating better contracts for female football players.

Polyethylene packaging and alternative materials in the United States: A life cycle assessment.

A comprehensive life cycle assessment was conducted to evaluate the potential environmental impacts of polyethylene (PE) packaging and its alternatives, including paper, glass, aluminum, and steel in the United States. The assessment focuses on five major packaging applications: collation shrink films, stretch films for pallet wraps, heavy-duty sacks, non-food bottles, and flexible food pouches. The study compares PE and the alternative packaging materials based on the following environmental impact categories: global warming potential (GWP), fossil energy use, mineral resource use, and water scarcity. The research integrates sales volume estimates for each application, examining the substitution ratios of PE-based materials and the GWP decrease capabilities of using PE as packaging material. The findings reveal that substituting PE for other packaging materials can lead to an average life cycle GWP emissions decrease of approximately 70%. This significant decrease highlights the potential GWP benefits of PE in the context of packaging solutions in the United States. We also provide a detailed analysis of the potential environmental impacts and trade-offs associated with PE and its alternatives. The insights gained from this study are intended to assist stakeholders and policymakers in making informed decisions that balance environmental impact mitigation with maintaining product functionality and achieving sustainability objectives.

Effects of long-term volleyball training on multimodal responses in adolescent female athletes: a follow-up study.

The aim of this study was to examine the effects of long-term (10 months) volleyball training on biochemical responses in adolescent female athletes since the cumulative effects of chronic training on this population are not yet clear. Twenty-one adolescent female volleyball players competing at the national level served as the participants. All athletes carried out volleyball training, which consisted of ball handling, specialized drills, and practical game-style exercises, including physical training in the school gymnasium. The average training cycle consisted of 6 days per week, with a total of about 2 to 2.5 hours of volleyball training per day. In order to determine the cumulative effects on autonomic, immune, renal function and bone resorption, salivary and urinary samples were collected before volleyball training on 3 consecutive days (days 1, 3 and 5) at months 0 and 10, respectively. No significant changes in body mass, salivary secretion rate, urinary albumin, L-type fatty acid binding protein and type I collagen cross-linked N-telopeptide concentration were found. In contrast, significant decreases were noted in salivary α-amylase activity (% change: -22.9), total protein (%change: -21.4), and immunoglobulin A concentration (% change: -20.1). The results of this study imply that the autonomic function after chronic volleyball training in adolescent female athletes may be enhanced due to training adaptation, although the immune function may be attenuated as a result of cumulative overtraining. Moreover, long-term volleyball training in adolescent female athletes appears to suppress bone resorption and not to induce cumulative damage to renal function.

Dually encapsulated LiMn0.6Fe0.4PO4 architecture with MXenes and amorphous carbon to achieve high-performance and ultra-stable lithium batteries

An LMFP@MXene@C cathode material was fabricated by electrostatic adsorption and in situ graphitization, providing optimized Li+ transmission and a stable structure featuring ultrahigh average capacity and cycle stability.

Develop the Precise Vacuum Seeder for Nursery Plug Tray Sowing by Using the Vacuum Cleaner

The manual sowing of vegetable seeds is the general practice of vegetable nurseries in Thailand. It is the slow and labour-intensive process that causes the low production capacity. This study aims to design and develop a vegetable seed sowing machine for 200-cell plug tray plantings to substitute human labor. The prototype utilizes the vacuum cleaner to develop the suction head pressure that simultaneously offers the 200 seeds-planting per tray. The vacuum seeder mechanism is composed of the suction head unit and seeds tray unit. The prototype is operated and controlled by the automation system for continuous planting. Cantonese vegetable seed is selected to evaluate the planting precision of the prototype. Based on the design parameters obtained in laboratory experiments, the optimal condition for planting the Cantonese vegetable seeds in the 200-cell plug tray is verified by adjusting two parameters the suction pressures and the nozzle implement type. On the other hand, the planting precision is indicated by the single seed sowing index. The results showed that the average quality of feed index is 70.53% when utilizing the large nozzle implement type with a vacuum pressure of 1019 Pa. The average working cycle time per tray and the machine capacity per hour are 51.0 seconds and 70 trays, respectively. Moreover, the prototype machine costs about 43% of the average cost of the existing commercial seeders in terms of cost-effectiveness.

Supplier Relationship Management in the Digital Age: Enhancing Supply Chain Resilience Through Blockchain Technology

Digital transformation has driven companies to enhance supply chain efficiency and resilience through innovative technologies. However, challenges such as a lack of transparency, low efficiency, and risks of operational disruptions remain significant barriers in Supplier Relationship Management (SRM). This study aims to explore the role of blockchain technology in improving transparency, trust, and supply chain resilience. Using a qualitative case study approach, data were collected through in-depth interviews with supply chain managers from three companies in Indonesia and supporting document analysis. The findings reveal that blockchain implementation enhances operational efficiency by up to 35%, reducing the average process cycle time from 10 days to 6 days. Additionally, transparency levels increased by 40%, reflected in the ability of supply chain participants to monitor information flow in real time. Trust among stakeholders also improved by 25%, attributed to encrypted data security and immutable transaction records. These findings confirm that blockchain strengthens supply chain resilience through three main dimensions: response, recovery, and adaptation. The contribution of this research lies in enriching the literature on the role of blockchain in SRM, particularly in the context of supply chain resilience. Furthermore, the results provide practical guidance for companies in designing blockchain implementation strategies to mitigate operational risks and enhance stakeholder collaboration

Video analysis of biomechanical risk factors for musculoskeletal disorders in loincloths female weavers Faso Dan Fani in Burkina Faso

Background The purpose of this study is to describe the kinematic characteristics of manual weaving related to the biomechanical risk factors for musculoskeletal disorders. Methods The welve professional female weavers participated in this study. The video recording of their workstations was performed perpendicularly in the sagittal and transverse planes in a synchronized manner, at about 2.45 m and for 5 minutes. The videos were then analyzed using the Kinove software. Statistical processing by the statistical SPSS 22 software. Results The results identified a succession of cycles, each with two important phases called the “interlacing” phase and the “winding/adjustment” phase. The average cycle time is 127.9 ± 11.7 seconds. The “interlacing” phase is the longest and concerns an average 80% of the cycle time or 103.5 ± 35.9 seconds. The segmental movements are mainly flexion-extension type with angular variations constantly above the acceptable limits. It is the same for the repetitiveness of the movements which solicit the upper limb and the trunk particularly. Conclusions These results recommend one of the actions to prevent musculoskeletal disorders including instructions on postures and frequencies of weaving movements as well as physical exercises adapted to the physical needs of practitioners.

Evaluating Variables’ Influence on Forwarder Performance and Fuel Efficiency in Mountain Salvage Logging Using an Automatic Work-Element Detection Method

Extreme climate events are increasingly damaging forests, particularly in Europe’s Alps. These disturbances lead to more damaged timber, necessitating rapid salvage operations to preserve timber value and protect ecosystems. However, salvage logging, though essential, raises concerns about its environmental impact, especially on soil conservation and forest regeneration. To mitigate these effects, best practices such as leaving logging residues and avoiding wet soils are recommended. Nevertheless, fuel efficiency remains a critical concern. This study focuses on addressing gaps in understanding forwarder productivity in salvage logging, considering factors such as assortment number, extraction distance, and payload. Utilizing Automatic Work-Element Detection (AWED) for data collection, this study enhances fuel efficiency analysis. Findings show that the average cycle time was 27.4 min, with 4.9 L of fuel consumed per cycle. Each cycle covered 241.3 m, extracting 11.7 m3 of timber, yielding a productivity rate of 31.6 m3 per machine hour and a fuel efficiency of 0.4 L per m3 and per 100 m. Traveling was the most time- and fuel-intensive task. Assortment type significantly impacted loading time and fuel consumption, with short sawlogs requiring fewer crane cycles. Key factors influencing productivity and fuel efficiency were average log volume, distance, payload, and slope.

Regulation of thermal transport by cycle structures in complex networks

The regulation of thermal transport in complex networks is a challenging topic. This paper focuse on thermal transport in the Erdős-Rényi network by adjusting two coefficients: the number of cycle structures and the cycle ratio. The results indicate that the increase of cycles in Erdős-Rényi networks leads to enhanced phonon localization and reduced efficiency in thermal transport. Further more, as the average cycle ratio increases, we observe an improvement of the network’s thermal transport efficiency, accompanied by thermal rectification phenomena. Finally, through the analysis of participation ratio, eigenvalue spectra, and node vibration time series, we clarified that the variations in phonon localization and the widths of the phonon spectrum are key factors influencing the thermal transport in complex networks. This work enables control of thermal transport by adjusting the structural characteristics of the network and provides further exploration and development of phonon localization in disordered systems.

A Νew Heuristic Optimization Approach to the Single Hoist Cyclic Scheduling Problem

This paper introduces an innovative heuristic optimization approach, referred to as Optimization Approach-Single Hoist Cyclic Scheduling Problem (OA-SHCSP), which aims to minimize the cycle time of the Single Hoist Scheduling Problem (SHCSP). The effectiveness of this proposed heuristic is compared with a previously established heuristic, the Earliest Starting Time (EST). The comparison results reveal that the proposed OA-SHCSP heuristic consistently outperforms the EST heuristic in minimizing cycle time, particularly when more than two products are produced simultaneously. Moreover, as the number of part tasks soaked during a cycle increases, OA-SHCSP demonstrates significantly improved computational efficiency over the EST heuristic. The reduction in average cycle time achieved by OA-SHCSP ranges from 28.73% to 60.29%, underscoring its effectiveness and potential for application in high-volume production environments.

Moult cycle and setal development of the Atlantic ditch shrimp Palaemon varians Leach, 1814 (Decapoda: Caridea: Palaemonidae)

Abstract The Atlantic ditch shrimp Palaemon varians Leach, 1814 is a common estuarine and brackish water species on Northern Atlantic coasts. Palaemon varians is an appealing model organism for studying arthropod developmental processes, such as moulting (ecdysis). Detailed morphological information on its moult cycle is still lacking, hence we have characterised the changes in the setal features corresponding to the moult stages of P. varians grown under laboratory conditions. The stages of the moult cycle were differentiated and described using microscopic analysis of the setae in the uropods of P. varians based on Drach’s classification system. Moult stages were defined as early and late post-moult (A and B), inter-moult (C), early-, mid- and late pre-moult (D0, D1, and D2), as well as ecdysis stage (E), the actual shedding of the exuvia. Average moult cycle duration was 8.7 days, where pre-moult accounted for the longest duration of 4.4 days on average. This study provides a morphological reference for determining the moult stage of P. varians without the use of invasive techniques, and thus it is well suited for repetitive observations of an individual to track the entire moulting process.

Mathematical Modeling of the Operation of a Hydrophoric Installation

Abstract In this paper, the performance of a pumping system is considered in its operation with a hydrophore vessel connected in parallel. The filling and emptying processes of the hydrophore and their influence on the flow rate to the system and the pump outlet pressure are experimentally investigated. An automated measuring system is used for the measurements of the flow rate and the pressure. That has cyclically recorded the values at equal time intervals. The measurement cycles are synchronized in time and the maximum errors of the measured quantities are known. From the experimental data, empirical relationships are obtained for flow rate and pressure as a function of time, as well as the relationships between the two quantities. The time periods of each of the two processes and the average cycle length are also empirically determined. Confidence intervals of the flow rate are constructed for vessel filling and emptying, respectively, and measurement errors were accounted for. Codes have been created to determine the filling time of a hydrophore vessel and to calculate confidence intervals for this type of pumping systems, thanks to which all calculations have been automated. The described dependencies can be used in planning future experiments.

Development, Integration, and Field Evaluation of a Dual‐Arm Ridge Cultivation Strawberry Autonomous Harvesting Robot

ABSTRACTStrawberry harvesting is a labor‐intensive and time‐consuming task, and the shortage of labor resources and high production costs have made strawberry harvesting robots a focus of attention in both academia and industry. This paper presents a dual‐arm strawberry harvesting robot suitable for ridge cultivation in polytunnels. The coordinated operation of the robot's software and hardware systems enables it to automatically harvest strawberries along the ridge. To ensure the integrity of the fragile fruit, a nondestructive end‐effector was designed that can directly separate and grip the stem, avoiding contact with the fruit itself. Additionally, a method based on composite models was introduced to accurately determine the location and tilt direction of the picking points, to address the randomness in the growth direction of the stems. Furthermore, the modular five degrees‐of‐freedom robotic arm is better suited to the harvesting task requirements. Field evaluation results show that the robot achieves harvesting success rates between 98.4% and 57.4%, and destructive harvesting success rates vary between 98.4% and 75.0% across four scenarios of different complexities. Overall, the success rates for nondestructive and destructive harvesting reach 78.8% and 87.2%, respectively. The average harvesting cycle in the dual‐arm working mode is 4.5 s per berry. Through an in‐depth analysis of the results obtained, this paper also discusses the existing limitations and future research directions.

Learning policies for resource allocation in business processes

Efficient allocation of resources to activities is pivotal in executing business processes but remains challenging. While resource allocation methodologies are well-established in domains like manufacturing, their application within business process management remains limited. Existing methods often do not scale well to large processes with numerous activities or optimize across multiple cases. This paper aims to address this gap by proposing two learning-based methods for resource allocation in business processes to minimize the average cycle time of cases. The first method leverages Deep Reinforcement Learning (DRL) to learn policies by allocating resources to activities. The second method is a score-based value function approximation approach, which learns the weights of a set of curated features to prioritize resource assignments. We evaluated the proposed approaches on six distinct business processes with archetypal process flows, referred to as scenarios, and three realistically sized business processes, referred to as composite business processes, which are a combination of the scenarios. We benchmarked our methods against traditional heuristics and existing resource allocation methods. The results show that our methods learn adaptive resource allocation policies that outperform or are competitive with the benchmarks in five out of six scenarios. The DRL approach outperforms all benchmarks in all three composite business processes and finds a policy that is, on average, 12.7% better than the best-performing benchmark.

Why they take the risk to perform a direct left turn at intersections: A data-driven framework for cyclist violation modeling

Bicycle crashes at intersection areas are posed a worrying traffic safety issue, and one of the main reasons for bicycle crashes is failing to avoid conflicts with motor vehicles and other bicycles. Clearly, cyclists are more exposed to risk if they perform a direct left turn (DLT) being mixed with left-turning vehicle under a left-turn phase. Owing to the lack of exposure data, the detection of DLT event and the mechanism behind the risky riding behavior have yet to be discovered. To bridge these gaps, this study proposes a DLT detection framework based on bike sharing trajectories. Moreover, this study seeks to understand the contributing factors to DLT behavior using the random parameters logit model with heterogeneity in means and variances (RPLHMV) to account for unobserved heterogeneity in the DLT cases dataset. Statistical analysis shows that DLT is most likely to occur on weekdays during peak periods under large commuting demand. As to what caused the DLT violations, law-obeying cyclists are more susceptible to external events, while risk-taking cyclists are subtly undermined by their habits. In addition, the model of RPLHMV reveals several significant contributing factors to the propensity of DLT violations, such as event time, available passing time for left-turning bicycles, and average cycling speed, whereas the indicator variables of actual waiting time, available passing space for left-turning bicycles, and preference for DLT violation become the emerging influential variables. This study is expected to help better understand DLT occurrence and propose countermeasures more efficiently for reducing cyclists’ DLT rate.

QLTI-21. STREAMLINING THE STUDY INTAKE PROCESS AT THE CANCER CLINICAL AND TRANSLATIONAL RESEARCH OFFICE (CCTRO)

Abstract Challenges in the Protocol Intake/Activation process at the Henry Ford Cancer Center, particularly during the budget negotiation and coverage analysis (CA) phases, hamper operational efficiency and financial prospects. This study aimed to improve budget time and process efficiency. Process flow mapping, Value Stream Mapping (VSM), and cause-effect analysis using a fishbone diagram were used to identify and analyze key bottlenecks, focusing on the budget negotiation and CA phases. Budget negotiation took an average of 121.5 days in 2023 due to multiple procedures and a lack of standardized practices. Delays ranged from 127.75 days in August to a low of 69.84 days in November of 2023. The budget build process averaged 13.31 days, with an additional 7.57 days for approval, totaling 20.89 days. The CA phase had an average cycle time of 10.82 days (range 2-10 days). To improve approval times, it was recommended to implement an Electronic Document Management System to automate routing, signing, and tracking of budget and CA-related documents, standardized budget templates to streamline negotiations, a detailed electronic checklist to streamline task lists for document collection and budget negotiation, automated reminders for internal and external stakeholders to ensure timely submission of necessary documents, and timely submission policies enforced by a dedicated finance member on committees. Newly developed Key Performance Indicators (KPIs) such as ‘time to collect documents,’ ‘time between committees,’ and ‘time for budget negotiation process,’ along with a dual tracking system in Excel, were proposed to monitor and improve these metrics. The recommendations are expected to significantly enhance the efficiency of the Protocol Intake/Activation process. By reducing the budget negotiation phase to less than 60 days and optimizing the CA process, faster study initiation, better resource utilization, and improved responsiveness to research opportunities will be achieved. This study underscores the critical need to address operational challenges in clinical trial management to enhance CCTRO’s capability to conduct timely and effective research.

Electrolyte Design Enables Stable and Energy‐Dense Potassium‐Ion Batteries

AbstractFree from strategically important elements such as lithium, nickel, cobalt, and copper, potassium‐ion batteries (PIBs) are heralded as promising low‐cost and sustainable electrochemical energy storage systems that complement the existing lithium‐ion batteries (LIBs). However, the reported electrochemical performance of PIBs is still suboptimal, especially under practically relevant battery manufacturing conditions. The primary challenge stems from the lack of electrolytes capable of concurrently supporting both the low‐voltage anode and high‐voltage cathode with satisfactory Coulombic efficiency (CE) and cycling stability. Herein, we report a promising electrolyte that facilitates the commercially mature graphite anode (&gt;3 mAh cm−2) to achieve an initial CE of 91.14 % (with an average cycling CE around 99.94 %), fast redox kinetics, and negligible capacity fading for hundreds of cycles. Meanwhile, the electrolyte also demonstrates good compatibility with the 4.4 V (vs. K+/K) high‐voltage K2Mn[Fe(CN)6] (KMF) cathode. Consequently, the KMF||graphite full‐cell without precycling treatment of both electrodes can provide an average discharge voltage of 3.61 V with a specific energy of 316.5 Wh kg−1−(KMF+graphite), comparable to the LiFePO4||graphite LIBs, and maintain 71.01 % capacity retention after 2000 cycles.

Electrolyte Design Enables Stable and Energy-Dense Potassium-Ion Batteries.

Free from strategically important elements such as lithium, nickel, cobalt, and copper, potassium-ion batteries (PIBs) are heralded as promising low-cost and sustainable electrochemical energy storage systems that complement the existing lithium-ion batteries (LIBs). However, the reported electrochemical performance of PIBs is still suboptimal, especially under practically relevant battery manufacturing conditions. The primary challenge stems from the lack of electrolytes capable of concurrently supporting both the low-voltage anode and high-voltage cathode with satisfactory Coulombic efficiency (CE) and cycling stability. Herein, we report a promising electrolyte that facilitates the commercially mature graphite anode (>3 mAh cm-2) to achieve an initial CE of 91.14 % (with an average cycling CE around 99.94 %), fast redox kinetics, and negligible capacity fading for hundreds of cycles. Meanwhile, the electrolyte also demonstrates good compatibility with the 4.4 V (vs. K+/K) high-voltage K2Mn[Fe(CN)6] (KMF) cathode. Consequently, the KMF||graphite full-cell without precycling treatment of both electrodes can provide an average discharge voltage of 3.61 V with a specific energy of 316.5 Wh kg-1-(KMF+graphite), comparable to the LiFePO4||graphite LIBs, and maintain 71.01 % capacity retention after 2000 cycles.