Where reviews and research have attempted to conceptualize readiness, their focus has been both broad, and longer term, spanning multiple constructs, including: self-efficacy; commitment; perceived organizational support; physical fitness; sense-of-community; technical competence; family-life; and job satisfaction Adams et al. The models related to individual readiness are still relatively few and often lack empirical support.
Hence the necessity of developing a suitable psychometric measure of acute readiness is increasingly clear. Psychometric research studies have examined different forms of readiness, including: exercise readiness e.
None of the existing scales span all the different roles fulfilled by military personnel - reaching beyond combat - which necessitated the development of a new specific measure. In combination, these different components may combine to form an overall indication of acute readiness. Further, important distinctions can be made between acute readiness versus attributes developed over time, such as skills-and-training, as well as a distinction between group-level constructs such as climate and individual states such as fatigue or freshness.
We set out to develop a scale to focus on acute, individual, multidimensional readiness — in order to when implemented detect short-term changes in individual and group capability. Aside from time-consuming and resource-heavy medical examinations, the main alternative to a psychometric approach for monitoring readiness would be the use of wearable devices to monitor physiological signals such as heart rate, heart-rate variability, skin temperature, and galvanic skin response Domb, ; Seshadri et al.
Biochemical markers are also available through the sampling of sweat and sometimes blood to capture metabolites and electrolytes Bandodkar and Wang, ; Lee et al.
Decreasing production costs, increasing portability and the opportunity for real-time monitoring has made these popular options. Nevertheless, these devices can demonstrate inconsistent reliability between different circumstances, and are often dependent on communications network, with implications for battery life and data-security Evenson et al. In many settings, including the military, construction, food processing, nursing and allied health professions, complications are caused via: a exposure to wide variations in temperatures; b frequent heavy usage; c impacts; and d challenges such as water, sweat, grit and sand.
Keeping such devices operational over long periods can generate a significant impost, for example, through charging, maintenance and software updates. Without access to suitable network connectivity or local information processing capabilities, the raw information gathered by these devices is often uninterpretable by the user, and over extended periods may simply be deleted or become outdated before it is uploaded.
Finally, in reviewing existing psychometric measures of relevant and related concepts, several key issues support the development of a new instrument. Measures such as stress-recovery e. Measures of current subjective state such as affect e.
The other related concept might be self-efficacy Bandura, ; Sherer et al. While clearly relevant to the concept of readiness, especially with reference to roles and skills, we argue that immediate readiness has a more specific focus than the broad judgment of being capable that typically informs self-efficacy.
Likewise, self-efficacy is more likely to be relatively stable over time Ryckman et al. A systematically developed measure of acute readiness, with items that are applicable across diverse professions and job roles, is necessary for timely, informative and psychometrically sound assessments of readiness.
We also sought to evaluate the correlations of ARMS factors to other related variables. Additionally, we sought to examine evidence for reliability and discriminant validity of the subscales of the ARMS. Second, we set out to evaluate the internal structure, internal consistency, and discriminant validity of the subscale scores of the new measure.
We targeted a sample of five to ten participants per item Anthoine et al. Seven participants declined to participate at the informed consent stage, and any corresponding data were destroyed. One participant spoiled their answers and was excluded.
Career length in the Army ranged from 0. The subsequent evaluation of convergent and divergent validity was conducted using the whole sample. Items were also developed to provide an overall appraisal of readiness. An initial pool of items was developed based upon the operational definition of acute readiness. Items were kept brief but not single word items , were not double-barreled in syntax, and did not borrow heavily from any one existing measure.
Reverse-scored items were included. The content of items was informed by existing self-report measures of readiness, affect, perceived task load, stress-recovery, coping, and fatigue e. The initial item pool is listed in Supplementary File 1.
We also presented and discussed the proposed approach to a group of senior stakeholders at a workshop held on 8th April Subsequently, task orders were issued from Australian Army Headquarters to make troops available for data collection visits lasting approximately 1-h. Data-collection took place in person, at locations across Australia, using paper-and-pen surveys — typically in groups of between 15 and personnel in one sitting.
Commanding officers were not required to be present, but some chose to attend and complete the task with their units see Participants, above. Prior to survey administration, participants were advised of the wider intention of the project to generate a readiness monitoring instrument and shown mock-ups of how such a system could look and be used in practice.
Participants were assured that were no right or wrong responses, reminded of the anonymity of their responses, and encouraged to respond honestly. We recorded the time of day that survey completion began, as well as the most recent task that the participant had completed, as well as how demanding they found that using the NASATask Load Index TLX. Only personnel who were on-base at the time of data collection were included. Participation in the study was voluntary, and this was emphasized through the informed consent process as well as in the small presentation preceding the data collection.
All participants completed a written informed consent form prior to taking the survey, which was administered in person immediately prior to the data collection. Participants were informed they could return to other tasks if they did not wish to participate, although — as implied above - several chose to complete the survey with their team and then withheld consent for the data to be used.
Exploratory factor analysis EFA identifies the dimensionality of constructs by examining relations between items and factors Netemeyer et al. For this reason, EFA is typically performed in the early stages of developing a new or revised instrument Wetzel, In this study, seven candidate factors were developed: a overall readiness b physical readiness; c cognitive readiness d threat-challenge readiness; e skills-readiness; f group readiness; and g equipment readiness.
This hypothesis was used to inform how we explored the structural pattern of the preliminary scale, along with a scree plot and eigenvalues Thompson, Scree plots are useful to estimate where a significant drop occurs in the strength of possible factors Cattell, ; Netemeyer et al. As such, ESEM is useful in clarifying key issues such as cross loading and potential shared error variance before moving to the CFA stage.
For CFA modeling, latent factors were permitted to correlate, with cross-loadings of items on unintended factors being constrained to zero. Similar to CFA, as the analysis progressed into evaluating ESEM models, items could load on their predefined latent factors, while estimating cross loadings and considering this in the development of the evolving model. The strength of factor loadings was informed by the recommendations put forth by Comrey and Lee — i.
Prior to the factor analyses, data were scanned for univariate normality regarding the assumption for the use of maximum likelihood estimation method. Median values for skewness and kurtosis for the 88 candidate items were 0. MLR yields robust fit indices and standard errors in the case of non-normal data and operates well when categorical variables with a minimum of five response categories are employed Rhemtulla et al. Having established the data were suitable for EFA, we continued to explore the data.
As such, we used MPlus to generate factor solutions between 7 and 14 factors, and reviewed the solutions in relation to: a the hypothesized factor structure; b feedback from the expert panel prioritizing conceptual clarity ; and c user-group workshop and stakeholder inputs for example prioritizing interpretability, brevity and parsimony.
By reviewing the multiple factor solutions simultaneously, we recorded which items consistently loaded together, and which items consistently cross-loaded, or failed to load meaningfully. For these analyses, we included CFA steps as they were helpful in comparing models and selecting items with strong primary factor loadings to ultimately inform the final ESEM model see also, Bhavsar et al.
Model misspecification was identified through assessments of standardized factor loadings and modification indices, in a manner similar to item reduction approaches used in previous scale development procedures e. Alongside these statistical criteria, we also considered the conceptual coverage of the items.
Items with standardized factor loadings below 0. As such, 56 of the 88 items were deleted in a systematic manner over several iterations. The resulting nine one-factor models each had excellent fit see Table 2.
The result of EFA in Study 1 was a refined measure that included 32 items arranged into nine factors see Table 3. Table 2. Model fit indices of different models developed during the ESEM process. Standardized factor loadings were significant and above 0. Four cross-loadings greater than 0. Subscale correlations ranged from 0. These were over 0. Table 4. Correlation table for concurrent and discriminant validity of study 2 — acute and short-term correlates.
Table 5. Correlation table for concurrent and discriminant validity of study 2 — traits and long-term correlates. Based on the theoretical rationale that resilience represents an array of traits that mitigate the effects of stress and demand on current readiness e. Confirmatory Factor Analysis CFA was conducted on the remaining sample of participants, randomly separated from the data used in Study 1. We selected a range of measures to assess convergent and discriminant validity of the newly developed ARMS.
In the following paragraphs, we report the Cronbach alpha reliability from the original validation or a cited revalidation: for internal reliability scores in the current study see Tables 4 , 5. To assess recent stress and load experienced by participants, we included three measures of recent stress: a chronic load using the item Demand-Induced Strain Compensation Questionnaire to assess both cognitive and emotional occupational strain Bova et al.
To assess traits that protect performance capability from the effects of stress i. This VAS was developed specifically for this study. Given the intended implementation by the stakeholders, we agreed that no further refinements were necessary to improve model-fit at this stage.
For concurrent validity, ARMS factors positively associated with each other, as well as positive affect, while negatively correlating with Kdistress and negative affect see Table 4. Nevertheless, TLX-frustration demonstrated small correlation with ARMS subscales, suggesting that the emotional experience of frustration may be more relevant in determining perceptions of immediate readiness than other forms of task-load see Table 4. As expected - noting that fatigue items were reverse coded - all ARMS subscales were positively correlated with the resilience-promoting traits of resilience CD-RISC , stress-mindset, self-control, and psychological wellbeing; while being negatively correlated with the total severity of recent hassles.
ARMS subscales were positively correlated with positive affect, and negatively correlated with negative affect and K distress, while meeting the criteria to demonstrate discriminant validity. We developed and validated a psychometric instrument suitable for assessing acute readiness: the ARMS. The intent behind this tool was to facilitate rapid, reliable indications from personnel themselves of current individual and group capabilities for immediate tasks; as well as the ability to monitor how individuals and groups respond to training and deployment challenges.
One data sample, conducted with Australian Army, was divided into two analyses, with findings supporting the key aspects of construct validity in this new psychometric tool. In Study 1, a total of 32 items for the ARMS received support in the forms of user-group endorsement, expert panel clarification, and then the demonstration of a factor structure that was largely consistent with expectations, including good model fit indices.
The factor structure was kept simple, with no additional modeling beyond simply tallying the nine factors, with no sharing of error variances or additional modeling performed. In Study 2, the factor structure developed in Study 1 was supported, showing acceptable fit in a fresh sample. Further, the concurrent validity of the ARMS was evaluated by examining the correlations between subscales, as well as with targeted constructs such as recent task-load, time-of-day, affect, distress and supervisor-ratings of readiness.
The subscales of the ARMS showed small-to-moderate intercorrelations as might be expected, and were also moderately associated with affect and Kdistress.
Most aspects of recent task-load did not associate to ARMS scores, although frustration in the most recent task was consistently correlated with ARMS scores.
The initial validation of a psychometric tool for monitoring readiness across a range of contexts and job-roles provides the basis for further cross-sectional and longitudinal evaluations.
While correlated, these items were not able to be modeled within single factors: i. As such a respondent could indicate physical or mental readiness-versus-fatigue to be any configuration of: a high:high; b high:low; c low:high or d low:low. In the studied population — perhaps faced by frequent combinations of physical and mental load, as well as certain cultural norms around admitting to weakness or vulnerability — it is possible that the observed pattern is unique to military: but that would largely support the need for further research to assess the suitability of the ARMS for different contexts.
Upon returning to the wider literature, however, we did find examples of this pattern in other research. For example, Boolani and colleagues have characterized different correlates of both trait Boolani and Manierre, and state fatigue-versus-energy Boolani et al. As such, our findings may be adding to a growing awareness that the experiences of energy and fatigue may be separate.
We developed the ARMS as a highly useable and easily interpreted scale. For many of the children and our volunteers, Kesem is a life-changing experience that spans far beyond a week at summer camp.
It fosters bonds and understanding that builds resilience, confidence, and lasting feelings of hope and joy. That's the magic of Kesem. While many programs, services, and communities support those coping with their own cancer diagnosis, these children often lack the resources, spaces, or peer-to-peer support tailored to help address their needs and experiences.
Across the country, we are reaching more children and families impacted by cancer every year. The image detected by the digital camera may be displayed on a monitor or computer. A transmission electron microscope can achieve better than 50 pm resolution and magnifications of up to about 10,,x whereas most light microscopes are limited by diffraction to about nm resolution and useful magnifications below x. However, because the SEM image relies on surface processes rather than transmission, it is able to image bulk samples up to many centimeters in size and depending on instrument design and settings has a great depth of field, and so can produce images that are good representations of the three dimensional shape of the sample.
The Scanning Transmission Electron Microscope STEM rasters a focused incident probe across a specimen that as with the TEM has been thinned to facilitate detection of electrons scattered through the specimen. Focused ion beam, also known as FIB, is a technique used particularly in the semiconductor industry, materials science and increasingly in the biological field for site-specific analysis, deposition, and ablation of materials.
However, while the SEM uses a focused beam of electrons to image the sample in the chamber, a FIB setup uses a focused beam of ions instead. Unlike an electron microscope, FIB is inherently destructive to the specimen. The abnormal type of female cone showed less than three seeds in one particular cone which has developed a restricted number of ovules, and the lack of success of pollination and fertilization of a normal 3-ovule cone The female cones may be dry and woody e.
Cupressus or succulent e. Juniperus, Thuja and have cone scales arranged in opposite pairs or in threes with one to many ovules Seeds number of J. The cone containing 1—3, rarely 4, seeds per cone of J. Through ripe seed cones from 50 J. Female strobili normally contain three ovules and thus produce 1—3 seeds although up to 6 is possible Seed cones of common juniper usually have three seeds varying 1—6 Filled seeds of J.
Ripe cone production correlated positively to seed set and seed predation but was independent of the percentages of empty and filled seeds The loss of seed per cone were due to predispersal seed predation and the abortion of seed Furthermore, the proportion of three-seeded cones was greater in the open than under forest shade From the literature, the ripen cones are usually mentioned with empty places with no seeds.
But it turns out that there are five chambers, but only three seeds 61 , 64 , Also, the seed quality of J. In contrast, the opposite was observed in plants growing in nutrient-poor environments Seeds number of the J. Through visual assessment of some vesicles filled and other vesicles empty seeds entirely empty or shrivelled contents, or embryo-less, the number in the majority of cones is five vesicles but not all of them contain the seeds We propose some possibilities for the use of the archaeological juniper cones in focus of the context; being buried with utensils, they could be used for the preparation of medical prescriptions, or they could be used for the flavoring of food.
The other possibility is related to the wrestlers' statuette and the juniper intake by athletes to increase endurance. In order to explain how and why the archaeobotanical materials have survived and preserved in an excellent conditions Fig. The location of the excavation site and soil condition were taken into consideration.
Plant fossils are generally preserved in environments that are very low in oxygen e. Plant fossils are commonly preserved in fine-grained sediment such as sand, silt, or clay. Organic material may also be protected in fine textured clay soils than coarse sandy ones.
Silt is the main constituent of soil texture that leads to poor drainage and a significant water holding capacity due to its texture taking into account the depth of buried metals and water level on the site The silt soil of Sais site, where the archaeobotanical materials were found, was advantageous for the preservation process. The rate of biological degradation of organic materials in soil was also affected by their molecular structure, while cellulose is consumed preferentially over lignin and other poly-phenols present in plant.
Both organic and inorganic matters are degraded in burial environments. Long-term burial changed the appearance and the chemical nature of the buried metal objects, resulting in the formation of corrosion of metals, and in some cases the complete destruction of the artefacts 70 , There are different parameters, which affect the corrosion process, i.
Soluble anions such as Cl - and SO4 — in high amount in burial environment cause severe corrosion in the long-term. In fact, the presence of high amount of soluble salt results in increasing conductivity of the soil and accelerating electrochemical reactions leading to corrosion of archaeological copper alloys The presence of soluble sulphate may due to the presence of calcium sulphate phases in the composition of soil because of gypsum used as a binder or plaster in the architecture.
The presence of sulphide metallic sulphide and its oxidation forms sulphuric acid, acidifies the soil and decreases pH Increasing acidity reduces organic degradation. In addition to the amount of corrosive anions in the soil, pH, the concentration of soluble salts and texture of the soil affect the preservation condition.
Basic copper sulphates are stable in acidic conditions. By changing the pH of the environment to an alkaline condition, they will transform to more stable compounds These products will transform into green coppertrihydroxychlorides basic copper chlorides in the presence of high concentration of soluble chloride ions 77 , This product is responsible for the green hue of the archaeobotanical specimens.
The antimicrobial effect of copper has been known for centuries 79 , 80 , 81 , so the presence of copper fragments in the find played a role in preventing organic decomposition. From the microanalysis results and mapping of elements distribution, it was found that silica and copper precipitated in cell walls Fig. Mineralization of plants by metals has previously been recorded This usually occurs when minerals carried in solution silica, carbonate, chloride, etc.
The presence of a hard coat and antioxidants in the plant are also possible causes of good preservation The initial silica deposition begins within cell walls rather than in the cell lumina. The initial silica precipitation involves the affinity of silicic acid for hydroxylgroups in hollocelluloses and lignin. This phenomenon was also observed in the studied specimens.
It can be concluded that there have been many factors affected the preservation condition of the archaeobotanical material, resulting in initial stages of fossilization and mineralization.
The unique preservation mode is greatly enhanced by the presence of metal fragments in addition to burial environment. In this study, unknown archaeobotanical materials from Sais archaeological site in Egypt, were identified.
They show similar cone shapes and anatomical features of Juniperus sp. The archaeobotanical cones composed of five rounded to oval seeds in cone shaped 0. The unique preservation condition is discussed as regards the burial environment; the kind and texture of soil, soluble anions such as Cl - and SO4 — , pH and the presence of metals.
Mohamed, W. An integrated approach for the documentation and virtual reconstruction of metal fragments. Birks, H. Plant macrofossil introduction. Google Scholar. In The Science of Roman History ed. Scheidel, W. Stanley, J. Submergence and burial of ancient coastal sites on the subsiding Nile delta margin, Egypt. Zhao, X. Holocene climate change and its influence on early agriculture in the Nile Delta, Egypt. Article Google Scholar. Sestini, G. Nile Delta: A review of depositional environments and geological history.
ADS Google Scholar. Stanley, D. Nile Delta: Recent geological evolution and human impact. Science , — Pennington, B. The fluvial evolution of the Holocene Nile Delta. Microbial decay of waterlogged archaeological wood found in Sweden applicable to archaeology and conservation.
Douterelo, I. Soil microbial community response to land-management and depth, related to the degradation of organic matter in English wetlands: Implications for the in situ preservation of archaeological remains. Weiss, E. Plant remains as a tool for reconstruction of the past environment, economy, and society: Archaeobotany in Israel. Israel J. Earth Sci. Challenges in the presentation and analysis of plant-macrofossil stratigraphical data. Archaeobotany 23 , — Mauquoy, D.
A protocol for plant macrofossil analysis of peat deposits. Mires Peat 7 , 1—5 Jacomet, S. Plant macrofossil methods and studies: Use in environmental archaeology. In Encyclopedia of quaternary science — Elsevier, Amsterdam, Takahashi, M. Poppinga, S. Hygroscopic motions of fossil conifer cones. Crepet, W. A mosaic Lauralean flower from the Early Cretaceous of Myanmar. Article PubMed Google Scholar. Feng, Z. Gondwana Res.
0コメント