Unit Time Research Articles

The effects of multimodal versus opioid-only analgesia on pain control and opioid exposure for inpatient acute pancreatitis: A retrospective cohort study.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Acute pancreatitis (AP) is a common gastrointestinal condition that carries a significant financial and physical burden for patients due to the painful presentation and frequent need for hospitalization. Treatment varies in the type and route of analgesic used. Unmanaged pain can lead to worsening health outcomes and prolonged admissions. Further research is needed to understand current practices for managing AP. This study was a retrospective, exploratory, single-center cohort study. Patients admitted to an internal medicine unit with AP from September 1, 2020, to December 31, 2021, were included. Our primary outcome was the change in pain scores during the first 24-hours after administration of the first pain-relieving medication. Secondary outcomes included change in pain scores within the first 12-hours, time to oral tolerance, characterization of analgesic orders, comparison of median pain scores by home analgesic usage, and specific inpatient opioid use. One hundred sixty-nine patients were screened, and 94 were included in the study. Forty-four patients were assigned to the multimodal cohort and 50 patients to the opioid-only cohort. Changes in pain scores per unit of time, assessed by a mixed-effects model, within the first 24 hours were -0.080 (SE, 0.018) in the multimodal cohort and -0.090 (SE, 0.014) in the opioid-only cohort (P = 0.780). Morphine milligram equivalents (MME) administered in the multimodal and opioid-only cohorts were 24.50 (interquartile range [IQR], 51.75) and 52.5 (IQR, 68.5) (P = 0.001), respectively. There was no significant difference in the change in pain scores between patients receiving multimodal therapy and those receiving opioids only. Significantly fewer MME were administered in the multimodal group, suggesting that multimodal therapy can be opioid-sparing in AP.

Wolf Predation on White‐tailed Deer Before, During, and After a Historically Mild Winter in Northern Minnesota

ABSTRACTIn many southern boreal ecosystems of North America, wolves are the primary predators of white‐tailed deer, and white‐tailed deer are the primary prey of wolves. Furthermore, wolf–deer systems have and will continue to become more common as white‐tailed deer range continues expanding northward in North America. Despite this, there is little information on kill rates of wolves on deer (i.e., the number of deer killed per wolf per unit of time)—a fundamental metric of wolf predation on deer—and how kill rates vary with deer density, wolf density, and environmental conditions. We estimated kill rates of wolves on deer before, during, and after a historically mild winter in the Greater Voyageurs Ecosystem, Minnesota, USA. Kill rates of wolves on deer were low (0.009–0.018 deer/wolf/day) in fall, peaked in February (0.050 deer/wolf/day), and quickly declined to 0 deer/wolf/day by April. The kill rates of wolves on deer we observed in winter were some of the lowest kill rates of wolves on deer that have been documented. Wolves in the Greater Voyageurs Ecosystem appeared unable to catch and kill a sufficient number of deer to meet their daily energetic requirements during Winter 2023–2024, and thus most wolves likely lost weight during winter, a period when wolves are typically in peak physical condition. The rates of wolf predation we observed appeared to be well below those needed to decrease deer population density in the GVE. Thus, our work, in combination with numerous other studies, indicates winter conditions are the primary driver of deer population change in northern climates.

Comparative study of turbulent round jet flows through direct numerical simulation at medium–high Reynolds numbers

This study examines a spatially evolving turbulent round jet at a Reynolds number of Re = 7000 based on the bulk velocity Ub and the orifice diameter D and a Prandtl number of Pr = 0.71 using direct numerical simulation (DNS). Statistical data are collected over 30 000D/Ub time units, including mean quantities, Reynolds stresses, heat fluxes, mixed moments, Reynolds stress and turbulent kinetic energy budgets, and probability density functions. Comparative analysis with a previous DNS at Re = 3500 (Nguyen and Oberlack, 2024a; 2024c) shows that the higher Reynolds number leads to a shift of the self-similarity to a greater distance from the orifice. A larger Reynolds number leads to higher magnitudes of different statistical moments, dissipation and production. In addition, a maximum visible in the near-field of the turbulence intensity components is smoothed at the larger Reynolds number. The probability density functions of the axial velocity and the passive scalar show Gaussian behavior on the centerline, but with larger standard deviations compared to the lower Reynolds number. The study highlights the significant impact of using a fully developed turbulent pipe flow profile as the inlet condition, which significantly reduces the size of the potential core by introducing initial turbulence intensities at the orifice.

Experimental study on the influence of cutting parameters on cutting characteristics of deep-sea seafloor massive sulfide

The research of seafloor massive sulfide cutting characteristics is in the initial stage, and experimental methods are rarely used to conduct research. In addition, the mechanism of cutting parameters influencing cutting characteristics is not clear. In order to clarify the influence mechanism, the influences of cutting depth and cutting velocity on cutting characteristics are studied experimentally. It is found that with the increase of cutting depth, the load fluctuation is more severe, the breaking yield is increased, the size of the chip is increased, the powdered percentage is decreased, and the externally expanded breaking zone of rock is wider. However, the cutting depth has little effect on the cutting angle, and the breaking angle is between 48° and 61°. With the increase in cutting velocity, the number of load fluctuations per unit of time increases significantly, and the size of the chip decreases. However, the breaking yield, powdered percentage, breaking angle and external expansion area remain basically unchanged. The research is of guiding significance to the optimization of the mining head structure and the selection of cutting parameters.

Post-disaster housing recovery estimation: Data and lessons learned from the 2017 Tubbs and 2018 Camp Fires

Post-wildfire housing recovery is a complex process for which systematically collected data remains scarce. Consequently, our ability to anticipate obstacles and plan for housing recovery from future events is limited. This study leverages housing permit datasets collected in Santa Rosa and Unincorporated Sonoma County, impacted by the 2017 Tubbs Fire, and Paradise, impacted by the 2018 Camp Fire. Permit and tax assessor data are combined to gain insights into the recovery processes for these communities. Although the percentage of rebuilt destroyed homes varies significantly between regions, the peak construction demand occurs around 1.5 years after each wildfire, with a substantial decline in the reconstruction rate after 2.5 years. Moreover, the pace of transition from permit application to reconstruction completion is similar across all three regions. Using this finding, we propose a methodology to forecast the number of parcels rebuilt per unit of time based on observations from prior events. A proof-of-concept application of the proposed methodology indicates that it estimates long-term housing recovery patterns based on permit application data collected within one year of the event. These findings indicate that a longitudinal housing recovery data database would help forecast housing recovery from future disasters by providing a source for early empirical validation of predictive models.

Operational Performance Evaluation Model for Food Processing Machinery Industry Chain

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Boosting Photocatalytic Hydrogen Evolution by a Light Coupling and Charge Carrier Confinement Strategy

AbstractHigh‐performance photocatalysis requires efficient light absorption and low charge carrier recombination rates. Herein, a light coupling and charge carrier confinement strategy is demonstrated to simultaneously enhance the light absorption efficiency and suppress the charge carrier recombination for high‐performance photocatalysis. The strategy is achieved by the delicate incorporation of catalysts into a dual‐core‐shell structure (e.g., CdS@SiO2@NaYF4:Yb/Tm), in which CdS (catalyst), SiO2, and NaYF4:Yb/Tm serve as shell, outer core, and inner core, respectively. Interestingly, the absorbed light can be confined within the CdS layer through multiple reflections between the CdS and SiO2 interfaces, achieving light confinement. This confinement endows a longer light residence time, enhanced light reabsorption and reutilization efficacy, and a higher concentration of photogenerated charge carriers per unit of time. Moreover, the insulating SiO2 can confine the photogenerated charge carriers within CdS layer, thus shortening their diffusion length for reduced recombination rates. Notably, when employed as the photocatalyst, this dual‐core‐shell structure showed a superb photocatalytic hydrogen evolution rate up to 74.67 mmol g−1 h−1, which is 11 times higher than that of pristine CdS. This work provides a new strategy for the design and synthesis of high‐performance photocatalysts.

Effects of Channelling a Peripherally Inserted Central Venous Catheter on Blood Flow

A catheter is a device that is inserted into the venous system to infuse treatment with controlled doses per unit of time. The study of its interaction with blood flow cannot be easily analysed with common analytical methods or different visualization techniques in real life. Computational Fluid Dynamics has become a very useful tool in a wide variety of fields of scientific study and has allowed access to the understanding of the anatomical and physiological functioning of the human body. In this work, Computational Fluid Dynamics is used to study the effects of inserting a catheter on blood flow and the quality of the mixture of blood with the various substances infused through this device. Results show that the insertion of the catheter not only does not worsen the blood circulation but improves it by reducing stagnant zones. Regarding mixture, a homogenization of the fluids in the venous area before their entrance to the heart was observed. Highest quality mixtures correspond to fewer infused fluids and at lower velocity.

Dynamic Spatial-Temporal Memory Augmentation Network for Traffic Prediction.

Traffic flow prediction plays a crucial role in the development of smart cities. However, existing studies face challenges in effectively capturing spatio-temporal contexts, handling hierarchical temporal features, and understanding spatial heterogeneity. To better manage the spatio-temporal correlations inherent in traffic flow, we present a novel model called Dynamic Spatio-Temporal Memory-Augmented Network (DSTMAN). Firstly, we design three spatial-temporal embeddings to capture dynamic spatial-temporal contexts and encode the unique characteristics of time units and spatial states. Secondly, these three spatial-temporal components are integrated to form a multi-scale spatial-temporal block, which effectively extracts hierarchical spatial-temporal dependencies. Finally, we introduce a meta-memory node bank to construct an adaptive neighborhood graph, implicitly representing spatial relationships and enhancing the learning of spatial heterogeneity through a secondary memory mechanism. Evaluation on four public datasets, including METR-LA and PEMS-BAY, demonstrates that the proposed model outperforms benchmark models such as MTGNN, DCRNN, and AGCRN. On the METR-LA dataset, our model reduces the MAE by 4% compared to MTGNN, 6.9% compared to DCRNN, and 5.8% compared to AGCRN, confirming its efficacy in traffic flow prediction.

The association between different leisure-time physical activity patterns and the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio in adults: national health and nutrition examination survey 2007–2018

BackgroundDespite the potential superiority of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) as a diagnostic and predictive marker, no study has investigated the link between different leisure-time physical activity (LTPA) patterns and the NHHR. This study aims to explore this relationship.MethodsData was extracted from the National Health and Nutrition Examination Survey (NHANES) cycles spanning from 2007 to 2008 to 2017–2018. Participants (N = 14,211) were classified into four groups based on their LTPA patterns: (1) inactive (LTPA = 0 min/week); (2) insufficiently active (LTPA < 150 min/week); (3) weekend warrior (LTPA ≥ 150 min/week within 1 or 2 sessions); and (4) regularly active (LTPA ≥ 150 min/week in more than 2 sessions). Weighted multiple linear regression analysis was employed twice, using inactive and regular active groups as reference groups, respectively. Weighted stratification analyses and interaction tests were performed by demographics.ResultsCompared to the inactive group, each additional unit of LTPA time was associated with a significant 0.23-unit greater decrease in the NHHR in the regularly active group [-0.23 (-0.29; -0.16)]. However, no significant decrease was observed in the “Weekend Warrior” [-0.11 (-0.22; 0.008)] or insufficiently active groups [-0.03 (-0.11; 0.04)]. Moreover, compared to the regularly active group, the insufficiently active [0.21 (0.13; 0.29)], “Weekend Warrior” [0.13 (0.004; 0.25)], and inactive [0.26 (0.20; 0.32)] groups had significantly higher NHHR. The associations between the NHHR and various LTPA patterns did not significantly differ by demographic factors, except for race.ConclusionThe regularly active pattern is significantly associated with a lower NHHR, but no significant difference in the NHHR was detected between the insufficiently active and “Weekend Warriors” patterns. The study suggests that frequency and regularity of PA are crucial for optimal lipid management, supporting clinical recommendations to meet or exceed 150 min of PA in more than two sessions per week.

Research on wind turbines preventive maintenance strategies based on reliability and cost-effectiveness ratio

Purpose The purpose of this study is to optimize the operational efficiency of the entire system by developing a reasonable maintenance strategy for wind turbines that improves component reliability and safety while reducing maintenance costs. Design/methodology/approach A hybrid incomplete preventive maintenance (PM) model based on boundary intensity process is established to give dynamic PM intervals for wind turbines using an iterative method with reliability as a constraint; the selection method of PM and replacement is given based on the cost-effectiveness ratio, which in turn determines the optimal number of PM for wind turbines. Findings The reliability is used to obtain the components’ maintenance cycle, and the cost-effectiveness ratio is used to select the number of maintenance times, thus, getting the optimal maintenance strategy. The validity of this paper’s method is verified by arithmetic cases, which provides a new method for formulating a reasonable PM strategy for wind turbines. Practical implications The wind turbine preventive maintenance strategy for Boundary intensity process proposed in this paper can scientifically formulate the maintenance strategy, optimize the cost-effectiveness per unit of time of the wind power generation system, and solve the problems of difficulty in formulating a reasonable maintenance strategy for the wind turbine components and high operation and maintenance costs. Originality/value In this paper, the authors describe the failure pattern by a Boundary intensity process, establish a hybrid incomplete PM model by introducing a failure intensity increment factor and an age reduction factor and establish a maintenance strategy optimization model with comprehensive consideration of reliability and cost-effectiveness ratio. Finally, the validity of the model in this paper is verified by arithmetic case analysis. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0153/

It’s Relative! The Cross-Modal Effects of Music Density on Perception of Product Size

Individuals inevitably make inferences concerning size when they consider an object presented without cues to its actual size. Recent studies show that structural differences in background music can influence consumers’ perceptions of product attributes through cross-modal correspondence. We introduce a new structural element of music, the “music event rate.” To this end, we make a distinction between the absolute density (notes per time unit) and the relative density (notes per measure or music event rate) and propose an influence of the latter on consumers’ perceptions of product size. Our study employs a 2 (notes per measure: four vs. eight) × 2 (music tempo: slow vs. fast) × 2 (music mode: major vs. minor) between-subject experimental design. Dependent variables are participants’ size estimates of three different food items (pictures of burger, pizza, wine bottle) presented online. The results show that the number of notes per measure has an influence on consumers’ size perception of food items insofar as a higher event rate or number of notes per measure in a music stimulus leads consumers to infer a smaller product size, whereas a lower number of notes per measure leads consumers to perceive products as larger. This cross-modal effects of the music event rate on product size perception represent a previously unexplored influence on consumer behavior.

Condition-based maintenance policy for shared service-oriented leased equipment

Due to growing consumer demands for immediacy, personalization, and high availability, equipment manufacturers are venturing into the sharing market with expanded shared leasing services. While selling usage rights of equipment, they provide additional services to the consumer in the role of equipment operators, such as free maintenance and swap. However, uncertain usage rates and return times in the shared model pose significant maintenance challenges. This paper proposes a personalized condition-based maintenance (CBM) policy accounting for these uncertainties and heterogeneous consumer usage patterns. By considering inspection, maintenance, and penalty costs, we minimize the long-run expected maintenance cost per unit of time for operators. In the numerical example, we compare our policy against fixed inspection interval CBM policy and non-fixed inspection interval CBM under average usage rate, demonstrating that personalized CBM reduces maintenance costs. Sensitivity analysis provides some managerial insights. Firstly, operators should adjust the number of free swaps strategically to manage the intensity of equipment swaps, and strike a balance between the increased maintenance costs due to the swap intensity enhancement and the improved user satisfaction and equipment availability resulting from the increased number of free swaps. Secondly, when the acceleration effect of imperfect maintenance on the degradation rate is strengthened, operators should prioritize reducing the frequency of imperfect maintenance and increasing the frequency of perfect preventive maintenance. Moreover, operators must make strategic investments in their maintenance actions, balancing maintenance costs and penalty costs to develop cost-effective imperfect maintenance improvement factors.

A seismic-risk-based bi-objective stochastic optimization framework for the pre-disaster allocation of earthquake search and rescue units

Accurately predicting earthquakes' time, location and size is nearly impossible with today’s technology. Severe earthquakes require prompt and effective mobilization of available resources, as the speed of intervention has a direct impact on the number of people rescued alive. This, in turn, calls for a strategic pre-disaster allocation of search and rescue (SAR) units, both teams and equipment, to make the deployment of resources as quick and equitable as possible. In this paper, a seismic risk-based framework is introduced that takes into account distance-based contingencies between cities. This framework is then integrated into a mixed-integer non-linear programming (MINLP) problem for the allocation of SAR units under uncertainty. The two minimization objectives considered are the expected maximum deployment time of different SAR units and the expected mean absolute deviation of the fulfillment rates. We recover the best vulnerability-adjusted routes for each size-location scenario as input to the optimization model using the dynamic programming (DP) approach as part of the broader area of reinforcement learning (RL). The results of the hypothetical example indicate that the comprehensive model is feasible in various risk scenarios and can be used to make allocation-deployment decisions under uncertainty. The results of the sensitivity analysis verify that the model behaves reasonably against changes in selected parameters, namely the number of allowed facilities and weights of individual objectives. Under the assumption that the two objectives are equally important, the model achieves a total deviation of %3.5 from the objectives with an expected maximum dispatch time of 1.1327 hours and an expected mean absolute deviation of 0.01.

PENERAPAN MODEL PEMBELAJARAN DIRECT INSTRUCTION TERHADAP HASIL BELAJAR SATUAN WAKTU SISWA KELAS II SD

This study aims to describe the improvement of learning outcomes of grade II elementary school students in Mathematics through the direct instruction model on the material of time units. The study adopted Classroom Action Research (CAR) with four (4) stages, namely planning, implementation, observation and reflection. The subjects of the study were 44 grade II students of Elementary School 1 Lembursawah, consisting of 24 female students and 20 male students. Data collection tools used repeat tests and observations. The data analysis technique used was the recapitulation of students' pretest and posttest scores from cycles I and II. The results of the study showed that the implementation of the direct instruction model can improve Mathematics learning outcomes of grade II students. It can be seen from the students' completeness in cycle I of 68% increasing to 84% in cycle II. It means that student learning outcomes increase gradually from cycle I to cycle II by 16%. Therefore, direct instruction model can improve students' understanding of the content of time units in the Mathematics subject of grade II elementary school.

Effect of intravenous different drugs on the prevention of restlessness during recovery period of pediatric laparoscopic surgery: a randomized control trial.

To explored the impact of dexmedetomidine and esketamine in mitigating restlessness during the postoperative recovery phase following laparoscopic surgery in children. 102 individuals aged 1 to 7years experiencing laparoscopic surgery were randomly allocated into three groups, each accepting 1μg/kg of dexmedetomidine, 0.3mg/kg of esketamine, or saline immediately at the end of carbon dioxide pneumoperitoneum. Emergence agitation(EA) occurrence was assessed by PAED scale and 5-point agitation scale. Pain was judged using Face, Legs, Activity, Cry, and Consolability (FLACC) scale. The recovery time, extubation time, and post-anesthesia care unit (PACU) stay time were recorded for all three groups. Patients administered 1μg/kg of dexmedetomidine (8.8%) and individuals given 0.3mg/kg of esketamine (11.8%) showed lower incidences of emergence agitation compared to those receiving saline (35.5%; P = 0.009). There was no statistically significant difference in the time to discharge from the PACU among the three groups of patients (P > 0.05). The recovery time and extubation time were notably extended in the dexmedetomidine group (40.88 ± 12.95min, 42.50 ± 13.38min) when compared to the saline group (32.56 ± 13.05min, 33.29 ± 11.30min; P = 0.009, P = 0.010). Following CO2 pneumoperitoneum in pediatric laparoscopic surgeries, the intravenous administration of 1μg/kg dexmedetomidine or 0.3mg/kg esketamine effectively lowers EA occurrence without extending PACU time.

Blood transfusion in injured older adults: A retrospective cohort study.

We asked how increasing age interacts with transfusion and mortality among older injured adults at our large regional trauma center. Older adults are increasing proportions of acute trauma care and transfusion, but the specific interactions of increasing age with blood product use are unclear. Trauma data (age, injury severity, mechanism, etc.) were linked with transfusion service data (type, timing and numbers of units) for all acute trauma patients treated at our center 2011-2022. Subsets of patients aged ≥55 years were identified by age decade and trends assessed statistically, p < 0.01. Of 73 645 patients, 25 409 (34.5%) were aged ≥55. Within increasing 10-year age cohorts, these older patients were increasingly female (32.2%-67.2%), transferred from outside facilities (55.2%-65.9%) and injured in falls (44.4%-90.3%). Overall, patients ≥55, despite roughly equivalent injury severity, were twice as likely to be transfused (24% vs. 12.8%) as younger patients and to die during hospitalisation (7.5% vs. 2.9%). Cohort survival at all ages and levels of transfusion intensity in the first 4 h of care were more than 50%. Through age 94, numbers of red cell and whole blood units given in the first 4 h of care were a function of injury severity, not age cohort. In our trauma resuscitation practice, patients aged ≥55 years are more likely to receive blood products than younger patients, but numbers of units given in the first 4 h appear based on injury severity. Age equity in acute resuscitation is demonstrated.

Inefficient star formation in high Mach number environments

Context. The star formation rate (SFR), the number of stars formed per unit of time, is a fundamental quantity in the evolution of the Universe. Aims. While turbulence is believed to play a crucial role in setting the SFR, the exact mechanism remains unclear. Turbulence promotes star formation by compressing the gas, but also slows it down by stabilizing the gas against gravity. Most widely used analytical models rely on questionable assumptions, including: i) integrating over the density PDF, a one-point statistical description that ignores spatial correlation, ii) selecting self-gravitating gas based on a density threshold that often ignores turbulent dispersion, iii) assuming the freefall time as the timescale for estimating SFR without considering the need to rejuvenate the density PDF, iv) assuming the density probability distribution function (PDF) to be log-normal. This leads to the reliance on fudge factors for rough agreement with simulations. Even more seriously, when a more accurate density PDF is being used, the classical theory predicts a SFR that is essentially 0. Methods. Improving upon the only existing model that incorporates the spatial correlation of the density field, we present a new analytical model that, in a companion paper, is rigorously compared against a large series of numerical simulations. We calculate the time needed to rejuvenate density fluctuations of a given density and spatial scale, revealing that it is generally much longer than the freefall time, rendering the latter inappropriate for use. Results. We make specific predictions regarding the role of the Mach number, ℳ, and the driving scale of turbulence divided by the mean Jeans length. At low to moderate Mach numbers, turbulence does not reduce and may even slightly promote star formation by broadening the PDF. However, at higher Mach numbers, most density fluctuations are stabilized by turbulent dispersion, leading to a steep drop in the SFR as the Mach number increases. A fundamental parameter is the exponent of the power spectrum of the natural logarithm of the density, ln ρ, characterizing the spatial distribution of the density field. In the high Mach regime, the SFR strongly depends on it, as lower values imply a paucity of massive, gravitationally unstable clumps. Conclusions. We provide a revised analytical model to calculate the SFR of a system, considering not only the mean density and Mach number but also the spatial distribution of the gas through the power spectrum of ln ρ, as well as the injection scale of turbulence. At low Mach numbers, the model predicts a relatively high SFR nearly independent of ℳ, whereas for high Mach, the SFR is a steeply decreasing function of ℳ.

Optimal two-time point longitudinal models for estimating individual-level change: Asymptotic insights and practical implications

Based on findings from a simulation study, Parsons and McCormick (2024) argued that growth models with exactly two time points are poorly-suited to model individual differences in linear slopes in developmental studies. Their argument is based on an empirical investigation of the increase in precision to measure individual differences in linear slopes if studies are progressively extended by adding an extra measurement occasion after one unit of time (e.g., year) has passed. They concluded that two-time point models are inadequate to reliably model change at the individual level and that these models should focus on group-level effects. Here, we show that these limitations can be addressed by deconfounding the influence of study duration and the influence of adding an extra measurement occasion on precision to estimate individual differences in linear slopes. We use asymptotic results to gauge and compare precision of linear change models representing different study designs, and show that it is primarily the longer time span that increases precision, not the extra waves. Further, we show how the asymptotic results can be used to also consider irregularly spaced intervals as well as planned and unplanned missing data. In conclusion, we like to stress that true linear change can indeed be captured well with only two time points if careful study design planning is applied before running a study.

The Challenger's Social Skills: Bengkalis Panglong Business

This article focuses on the social skills possessed by the challengers, in this case, charcoal panglong (a place for wood processing and charcoal production) owners, entrepreneurs, and their workers who are able to survive the regulations on the utilization of mangrove forests. The battle in this field began in the days of the Dutch government. The purpose of this study is 1) to reveal how the contestation of stability and change in the charcoal panglong business in Bengkalis. 2) to analyze the social skills possessed by the owner of the charcoal panglong and his workers, hereinafter referred to as challengers, in maintaining the existence of his business until now. The ability to maintain the charcoal panglong business and its business existence. A series of research studies using a qualitative approach, using interviews and observations, were conducted by the author to reveal a series of strategic action fields in the forestry business. The findings obtained show that challengers have always competed with incumbents (mangrove forest policies and regulations) and governance units for a long time. This field contestation has occurred since 1853, starting from the time the Dutch government established a panglong in Bengkalis to meet the demand for wood and charcoal from Singapore and Malaysia. The challenger always maintains its business existence by fulfilling all obligations as a holder of a community forest license granted by the president and also as a charcoal export license holder to Malaysia; of course, to meet these export needs, another skill it has is maintaining a stable supply of charcoal for export. The patron client relationship is one of the challenger's skills in maintaining good relations with the local community and its workers. The market field analysis using Fligstein and McAdam's Field Theory of Strategic Action Field (SAF) helps explore the elements of social skills in SAF so that the structure of stability and change in the forestry charcoal panglong business arena can be illustrated more clearly.