Variation In Performance Research Articles

Legumes vary strongly in their quality as hosts for parasitic plants: interactions between the root hemiparasite Rhinanthus alectorolophus and 30 legume species.

Host identity can strongly affect the performance of root hemiparasitic plants. Legumes have frequently been observed to be particularly beneficial hosts and it has been suggested that they are in general good hosts due to their association with rhizobia, but exceptions have been observed. We studied the interactions of the root hemiparasite Rhinanthus alectorolophus with 30 legume species. We related parasite performance and morphology to traits of uninfected hosts and the number and size of haustoria. We also analysed sections of haustoria quantitatively using morphometrics. There was enormous variation in the biomass and other traits of R. alectorolophus with the different legume species. The suitability of a legume species as a host had a significant phylogenetic component (Pagel's λ= 0.51). Parasite performance increased with the biomass of uninfected hosts. In contrast, host root traits explained little of the variation in parasite performance and there was no anatomical evidence of defence against infection. Parasite biomass was very strongly and positively related to the number of haustoria formed, but part of the variation due to host identity could not be explained by the host traits studied and the number of haustoria, suggesting a role for variation in the quality of compounds provided by the hosts. Damage to the hosts increased with mean parasite mass, but some legumes were tolerant of parasite attack. Sensitivity of the hosts to parasitism showed only a very weak phylogenetic signal (λ < 0.01). Legumes are not universally good hosts for root hemiparasites. Instead their quality as hosts ranges from very beneficial to very poor. Moreover, clades within the legumes differ in their suitability as hosts for hemiparasites. Parasites grow best with fast growing legumes that quickly produce large root systems with which many and large haustoria are formed.

Evidence of a circadian variation in 10-km laboratory running time-trial performance, where a standardised approach has been employed

ABSTRACT Diurnal variations in time-trial performance have been shown in people living normally, where a “standardised protocol” has been employed to reduce bias. We tested the hypothesis that a circadian variation exists for a 10-km running laboratory-based time-trial, where such a standardised approach is used. Twelve recreationally active adult males were recruited. The participants completed three familiarisation time-trials to the best of their ability at a self-selected pace and six 10-km time-trials at 06:00, 10:00, 14:00, 18:00, 22:00 and 02:00 h. Each session was separated by 7-days. Participants were allocated into 6 groups due to finish times (FT); sessions were counterbalanced in order of administration. A cosine fit for resting intra-aural temperature and FT both showed a significant circadian rhythm (p < 0.05) with mesor, amplitude and acrophases of 36.61°C vs 2994 s, 0.34°C vs 149 s; and 17:29 vs 18:44 h:min, respectively. The parallelism of temperature and FT agrees with previously published research. The finding of a 24-h rhythm in 10-km FT (5.0%, d = 0.80; power = 100%) concurs with that of a shorter distance where “standardised protocols” have been employed (4-km, 2.6%, d = 0.34). This finding has implications for scheduling of competition and training. Whether this variation is apparent in other populations, however, is unclear.

Evaluating the Strengths and Limitations of Structured Modified Rankin Scale Validation Studies - A Systematic Review.

Variations in performance of structured modified Rankin Scale (mRS) questionnaires in people with stroke within different cultural and language settings have not been systematically assessed. We systematically reviewed all studies of structured mRS questionnaires compared to in-person unstructured mRS evaluation scores. We searched PubMed and Web of Science for studies that evaluated structured mRS questionnaires against in-person unstructured mRS evaluations among people with stroke. Studies were analyzed for country of investigation, mRS self-assessment modality, care setting (inpatient vs outpatient), concordance between structured and unstructured mRS scores, and risk of bias. We identified 13 structured mRS questionnaire validation studies across all continents except Africa. The telephone mRS questionnaire was most commonly used. Average time between unstructured and structured assessments was 14 days. The weighted kappa agreement between structured and in-person unstructured scores ranged from moderate to very good (Kw range: 0.56-0.90), though unweighted kappa scores were significantly lower (K range: 0.27-0.68). Discrepancies between structured and in-person unstructured scores tended to result from patients at the scale extremes. Patients with good mRS outcomes (mRS ≤2) tended to rate themselves better on structured questionnaires than their clinicians rated them on unstructured evaluations while those with poor outcomes (mRS ≥3) tended to rate themselves worse than their clinicians. Major limitations across studies included sampling bias in inpatient settings, time delays between in-person unstructured and structured mRS assessments, and differences in the formatting of unstructured mRS assessments. While structured mRS questionnaire validation studies have generally displayed good agreement with in-person unstructured outcomes, significant discrepancies exist for patients with very poor and very good outcomes. Future studies should limit time between mRS assessments and better understand reasons for differences in structured and unstructured assessments. Further, data on validity of structured mRS tools are lacking from much of the world, especially Africa. 1K01TW011771-01A1 (Saylor).

Markerless motion capture in sport: panacea or Pandora’s box?

ABSTRACT This paper critically appraises the utility of markerless motion capture in the context of skill development and sports performance enhancement. If markerless motion capture is to be useful in a profiling or monitoring capacity, the amount of measurement error needs to be smaller than the amount of movement variability over iterative performance trials. Current evidence suggests that it is unlikely that any existing markerless system satisfies this requirement. The resolution of this issue would, in principle, enable technical errors to be more easily pinpointed and performance variation to be better explained. However, decomposing movement variability into its functional and dysfunctional components is not only a nontrivial undertaking for most practitioners, the practical consequences of doing so are limited because synergies are self-organising entities and any attempt to micro-manage their constituent degrees of freedom will likely have deleterious effects on performance. Biomechanical measurements technologies, including markerless motion capture, may be best used to support search strategies employed by coaches and athletes.

The Impact of Human Resource Management Practices on Public Institutions’ Performance: Case of Muhanga District, Rwanda

This research set out to examine the impact of human resource management practices on organizational performance, with a case study of Muhanga District in Rwanda. This study was guided by the Human Capital Theory and the Abilities, Motivation, and Opportunity (AMO) Theory. For this study, 243 participants were chosen at random from 20 public organizations. The inquiry was conducted using an explanatory research design. Employees at all levels of management were surveyed using a five-point Likert scale. The data obtained were analyzed descriptively using frequencies and percentages, as well as inferentially using correlations and regressions. The findings show that human resource practices significantly impact organizational performance. Recruitment and selection (β = 0.827, p = 0.000), compensation and rewards (β = 0.695, p = 0.000), and training and development (β = 0.698, p = 0.000) all show positive effects on performance. The R-squared value of 0.7942 indicates that 79.42% of the variation in performance is explained by these practices. Correlation analysis also reveals strong positive relationships between HR practices and organizational outcomes. Control variables, education (p = 0.046) and marital status (p = 0.035), are statistically significant. It is thus evident that training and development, compensation and rewards, and selection and recruitment are three separate factors that have considerable impacts on public organizational effectiveness. Therefore, it was concluded that institutions in Rwanda should prioritize government entities and other organizations consistently investing in their employees' professional growth through training and development programs. This study also recommended that organizations devise a continual incentive and pay program for their staff, with the Human Resources team being responsible for all hiring decisions.

Segmentation of cortical bone, trabecular bone, and medullary pores from micro-CT images using 2D and 3D deep learning models.

Computed tomography (CT) enables rapid imaging of large-scale studies of bone, but those datasets typically require manual segmentation, which is time-consuming and prone to error. Convolutional neural networks (CNNs) offer an automated solution, achieving superior performance on image data. In this methodology-focused paper, we used CNNs to train segmentation models from scratch on 2D and 3D patches from micro-CT scans of otter long bones. These new models, collectively called BONe (Bone One-shot Network), aimed to be fast and accurate, and we expected enhanced results from 3D training due to better spatial context. Contrary to expectations, 2D models performed slightly better than 3D models in labeling details such as thin trabecular bone. Although lacking in some detail, 3D models appeared to generalize better and predict smoother internal surfaces than 2D models. However, the massive computational costs of 3D models limit their scalability and practicality, leading us to recommend 2D models for bone segmentation. BONe models showed potential for broader applications with variation in performance across species and scan quality. Notably, BONe models demonstrated promising results on skull segmentation, suggesting their potential utility beyond long bones with further refinement and fine-tuning.

A Study on the Factors Influencing Rank Prediction in PlayerUnknown’s Battlegrounds

This study analyzes the key factors influencing player rank prediction in PlayerUnknown’s Battlegrounds (PUBG), using machine learning models to evaluate in-game performance. By examining variables such as “walkDistance”, “boosts”, and “weaponsAcquired”, the study identifies these as critical predictors, with “walkDistance” emerging as the most significant across all match types. Utilizing models including random forest (RF), gradient descent (GD), extreme gradient boosting (XGBoost), and feedforward neural network (FNN), the analysis reveals performance variation by match type: XGBoost achieves the highest accuracy in solo matches (88.07%), GD performs best in duo matches (84.75%), and RF records the highest accuracy in squad matches (78.21%). These findings provide valuable insights for game developers in balancing gameplay and offer personalized strategic recommendations for players. Future research may enhance predictive performance by incorporating additional variables and exploring alternative models applicable to PUBG and similar battle royale games.

A Performance-Based Adaptation Index for Automated Insulin Delivery Systems.

Automated insulin delivery (AID) algorithms can benefit from tuning of their aggressiveness to meet individual needs, as insulin requirements vary among and within users. We introduce the Performance-Based Adaptation Index (PAI), a tool designed to enable automatic adjustment of an AID system aggressiveness based on continuous glucose monitoring (CGM) metrics. PAI integrates two CGM-based metrics-one for hypoglycemia and another for hyperglycemia exposure-over a previous time window into a single index (). We propose two methods to compute : one based on time in range (TIR, 70-180 mg/dL), and the other on glycemic risk indices. Using , we developed a multiplicative strategy to adjust the AID system's aggressiveness, accounting for situations where cannot be reliably calculated. The feasibility of this method was assessed in-silico using the UVA/Padova Type 1 Diabetes Simulator and our full closed-loop algorithm (UVA-model predictive control (MPC)) across five scenarios: optimal tuning (baseline), conservative and aggressive tunings, and temporary and permanent changes in insulin needs. Glycemic outcomes were evaluated from the simulated glucose traces. Negligible performance variations were observed in the baseline scenario. For the conservative scenario, adjusting improved TIR (35.1% vs 71.8%) and increased total daily insulin (32.1 U vs 41.2 U). Conversely, for the aggressive scenario, it reduced hypoglycemia exposure (TBR: 2.6% vs 1.4%) and overall insulin usage (45.6 U vs 43.0 U). In-silico results demonstrated the safety and efficacy of using PAI to automatically tune the UVA-MPC controller, achieving TIR values above 70% under fully closed-loop conditions and across various physiological states. Clinical validation of these results is warranted.

Ultra-fast terahertz optical switch based on Metal vanadium dioxide

Abstract In current research, the reflection and absorption characteristics of optical switches in optical systems are often limited by the material's response speed and tunable range. We propose a novel metal grating structure with phase-change material to overcome these limitations. This paper proposes a tunable ultrafast terahertz optical switch based on vanadium dioxide (VO₂), composed of a VO₂ layer, a dielectric layer, and metal, with the VO₂ layer located on top of the plasmonic (Au) thin film. The optical performance variations in different states are revealed by analyzing the absorption rate, electric field distribution, and light absorption time of VO₂ before and after phase transition. VO2 exhibits a promising phase transition for actively controlling terahertz waves, with the insulator-to-metal transition used to switch the coupling between surface plasmon modes and normally incident electromagnetic waves on and off. These optical switches enable ultrafast switching, as the VO2 phase transition occurs on the femtosecond timescale. Experimental results indicate that the absorber demonstrates near-perfect absorption peaks, achieving absorption rates as high as 99.99%. The absorption efficiency modulation depth before and after the phase transition can reach 99.92%, allowing the absorber to achieve tunability. The reflectivity of VO2 is about -0.38 dB before the phase transition, and it significantly increases to -23.3 dB after the transition, with a switching ratio of 22.92 dB. This significant reflectivity change is attributed to the VO₂ phase transition, leading it to reflect light signals at high temperatures, preventing their transmission. The electric field diagrams and light absorption time analysis further support this conclusion, demonstrating that VO₂ material can efficiently switch optical signals by modulating temperature. This research offers new approaches for developing high-performance, fast-response terahertz optical switches, with potential applications in future optical communication and signal processing.

Improved Uniformity and Processability of Inkjet-Printed Single-Walled Carbon Nanotube Thin-Film Transistor by Introducing Cellulose Dispersant.

Solution-processed thin-film transistors (TFTs) based on single-walled carbon nanotubes (SWCNTs) hold great potential for next-generation electronics owing to their remarkable electrical, mechanical, and optical characteristics. However, challenges in efficiently dispersing SWCNTs hinder scalable fabrication. Conventional methods using surfactants improve SWCNT dispersion but lead to degradation of device performance due to increased contact resistance between the SWCNTs. Furthermore, the surfactant removal process induces unexpected characteristic nonuniformity by residual surfactant and network impairment. Here, we propose a facile and effective strategy for achieving superior performance uniformity in inkjet-printed SWCNT TFTs by using cellulose as a dispersant for SWCNTs. Cellulose-based SWCNT ink exhibits excellent dispersibility and stability, preserving the intrinsic electronic properties of SWCNTs while enabling optimal droplet formation for inkjet printing by adjusting the cellulose concentration. Based on the thermal decomposition characteristics of cellulose, we form a uniform SWCNT random network channel without affecting the nanotube network by selectively removing cellulose through a simple annealing process. As a result, the SWCNT TFTs fabricated on a 4-in. wafer substrate show significant improvements in characteristic uniformity, with a reduction of over 35% in performance variation, and exhibit strengths in switching performance compared to conventional surfactant-based SWCNT TFT fabrication methods.

Variations in the Diagnostic Performance of Transurethral Resection of Bladder Tumor with Photodynamic Diagnosis According to Surgical Experience: A Retrospective, Single-Center Study

BackgroundTo investigate variations in diagnostic performance of photodynamic diagnosis (PDD) according to surgical experience. MethodsData were extracted from patients having pT1 or lower primary tumors that underwent PDD-assisted transurethral resection of bladder tumors (TURBT) with orally 5-amibolevulinic acid at our institute. Surgical experience was categorized by urological experience (first-year and second-year) and PDD experience (<10, 10-19, and ≥20 cases). Sensitivity, specificity, and accuracy rates were calculated based on PDD or white light (WL) findings and pathologic diagnosis. The bladder neck, trigone, and prostatic urethra were defined as areas with a high probability of tangential effect. ResultsA total of 108 patients and 343 specimens were extracted. The second-year surgeons had significantly higher accuracy rates than first-year surgeons (81.5% vs. 69.0%, p=0.013), while PDD experience did not significantly affect accuracy rates (76.5, 75.5, and 69.0%). In addition, the accuracy rate was also significantly lower in tangential effect areas (59.6% vs. 80.8%). Multivariate analysis identified urological experience as a significant factor improving accuracy rate (odds ratio [OR] 2.14) while tangential effects substantially reduced accuracy rate (OR 0.37). Notably, combining both PDD and WL resulted in a sensitivity exceeding 94%, even in first-year urology residents and tangential effect areas. ConclusionsUrological experience had a greater impact on diagnostic performance of PDD compared to PDD experience. The combination of PDD and WL findings may improve sensitivity and reduce the possibility of missed diagnoses for less experienced urology residents.

The hematopoietic function, histological characteristics, and transcriptome profiling of Wanxi white geese ovary during nesting and late-laying stages.

Despite several factors influencing reproduction in geese, but the precise molecular mechanisms of egg cessation are not fully understood. In the present study, the hematopoietic parameters and serum hormone levels in Wanxi white geese were analyzed. RNA-Seq was utilized to identify the differentially expressed mRNAs (DEGs) and lncRNAs (DE lncRNAs) in the ovarian tissues associated with nesting in geese during the late-laying and nesting periods. Triglyceride (TG) and alkaline phosphatase (ALP) levels were higher in late-laying geese, while white blood cell (WBC), neutrophil (NEU), hemoglobin (HGB), and hematocrit (HCT) levels were significantly lower in late-laying geese. Serum levels of luteinizing hormone (LH), estrogen (E2), and progesterone (P4) increased significantly during the late-laying period, whereas prolactin (PRL) level was lower in the late-laying period than the nesting period. During the late-laying period, geese had a clear follicular hierarchy, with ovaries exhibiting mature and primary follicles. In the nesting period, the ovaries were degenerated and had many primary follicles without follicular development. Analysis of mRNA-lncRNA expression revealed 1,257 DEGs between the nesting and the late-laying stages, of which 841 were up-regulated and 416 were down-regulated DEGs. A total of 340 DE lncRNAs were identified between the nesting and the late-laying periods, with 113 being up-regulated and 227 down-regulated lncRNAs. DEGs, including TMEM, DRD3, IGFBP7, MAPK13, GnRHR2, HECTD3, KCNU1, OPRD1, and VCAM1, along with DE lncRNAs, including XR_001203613.1, XR_001206155.1, XR_001207759.1, XR_001213571.1 and XR_001214368.1 participate in reproduction in geese. Correlation analysis indicated that the cis-regulation of XR_001213096.1-ITPR3, XR_001203613.1-GALNT15, XR_001206155.1-COL6A3, XR_001207759.1-ANKS1B, and XR_001214368.1-VPS45 participate in the molecular mechanisms underlying nesting in geese. Functional enrichment analysis revealed the DEGs and DE lncRNAs associated with focal adhesion, extracellular matrix (ECM)-receptor interaction, cell adhesion molecules (CAMs), and PI3K-Akt signaling pathways, were responsible for the differences in the ovaries between the nesting and late-laying periods. This study offers valuable information on the roles of genes and lncRNAs, and the mechanisms underlying variations in reproductive performance between the late-laying and nesting periods.

Effect of laser surface treatment on microstructural evolution and mechanical properties of a Co–Cr–Fe–Ni–Mo medium–entropy alloy

In this study, we explored the influence of laser surface treatment on the microstructural evolution and mechanical properties of a Co17.5Cr12.5Fe55Ni10Mo5 medium-entropy alloy. After laser scanning on the cold-rolled alloy, a heterogeneous microstructure with Mo-rich μ-precipitates formed along the depth from the surface. Notably, laser processing parameters, including scanning speed and the number of scans, affected the macroscopic heterogeneity in the microstructure of the alloy, such as the thickness of the columnar, recrystallized, partially-recrystallized, and non-recrystallized layers. Furthermore, the microstructural features of the laser-treated alloys with a heterogeneous distribution of grains, cellular structures, and precipitates, contributed to the mechanical response of the alloys. As the heat input from the laser heat source increases, the grain coarsening and the absence of non-recrystallized layer have a greater impact on the strength of the laser-treated alloys, even if the precipitates distributed deeper from the surface. These microstructural modifications through laser surface treatment are linked to variations in the mechanical performance of the alloys, indicating that it can be an effective method to tailor the mechanical properties of structural materials.

Stereochemical tuning, post-synthesis crosslinking and quaternizing to tune the membrane performance of ultra-stable polyamine nanofiltration membranes

Solvent resistant and pH-stable nanofiltration membranes play a crucial role in solvent or water reuse across various industries, including pharma, chemical, dairy and mining, where stringent pH conditions and chemical stability are imperative. Previous research introduced a chlorine-resistant top-layer for nanofiltration membranes, using 1,2,4,5-tetra(bromomethyl)benzene and 1,2-diaminocyclohexane, with also exceptional stability at extreme pH values and a broad solvent resistance thanks to its crosslinked nature. To further optimize this remarkably stable and versatile membrane material, the unique property of 1,2-diaminocyclohexane, i.e. its stereochemistry, is employed here to manipulate membrane properties through diastereomerism and enantiomeric excess. Filtration experiments employing different 1,2-diaminocyclohexane isomers revealed significant variations in membrane performance, emphasizing the impact of stereochemistry on separation performance. Adjusting the enantiomeric excess of 1,2-diaminocyclohexane resulted in notable changes in membrane permeability and rejection, highlighting the general power of stereochemical control in membrane synthesis. Additionally, post-synthesis modifications, including further crosslinking and quaternization, allowed to tune the membrane structure and performance in both aqueous and solvent media, offering opportunities for optimization towards specific applications. SEM and XPS providing insights into membrane morphology and composition, confirmed the influence of stereochemistry and post-synthesis modifications on membrane properties. These findings demonstrate the efficacy of stereochemistry manipulation and post-synthesis techniques in tailoring pH-stable and solvent resistant nanofiltration membranes for specific applications, paving the way for advanced membrane design.

The Relationship of Teacher Perceptions of Educational Standards and Madrasah Head Leadership Style in Improving Teacher Performance

This research aims to discover: (1) The influence of teacher perceptions about educational standards on teacher performance. (2) The principal's leadership style influences teacher performance. (3) The influence of teachers and the principal's leadership style on teacher performance. This research focuses on Madrasah Ibtidaiyah Negeri (MIN) in West Tulang Bawang Regency, Lampung. This research method includes correlational/associative with a quantitative approach. Data collection techniques are carried out through observation, questionnaires, and documentation. Meanwhile, in obtaining the data that has been received, there is an influence of teacher perceptions about educational standards and the principal's leadership style on teacher performance. First, the regression analysis calculated t value reached 2.594, exceeding the t table value of 0.320 with a significance of 0.014, lower than 0.05. In addition, the teacher's perception of educational standards (R Square) is 0.157, showing that the principal's leadership can explain around 15.7% of teacher performance. Second, the regression analysis calculated t value for teacher perceptions reached 3.583, exceeding the t table value of 0.320, with a significance value of 0.001 which is less than 0.05. Third, the magnitude of the influence of teacher perceptions on educational standards is (R Square) 0.263, which indicates that around 26.3% of teacher performance can be explained by teacher professionalism. Third, with the calculated F regression results of 9.437, greater than the value of 3.27, with a significance value of 0.001, less than 0.05. In addition, the influence of teachers' perceptions of educational standards and principals' leadership styles (R Square) of 0.350 indicates around 35% of variation in teacher performance.

The Impact of Short-Term Debt on the Performance of Manufacturing Companies Listed on the Ghana Stock Exchange

Abstract: This study examines the impact of short-term debt on the financial performance of manufacturing companies listed on the Ghana Stock Exchange over an eight-year period (2015–2023). Using a combination of descriptive and causal research designs, the study utilizes secondary data from audited financial statements to investigate the relationship between short-term debt and firm performance, measured through Return on Assets (ROA). The findings reveal a significant but negative correlation between short-term debt and ROA, indicating that higher reliance on short-term financing may adversely affect profitability. Conversely, firm size demonstrates a positive but weak association with performance. Regression analysis confirms that short-term debt and firm size account for 9.9% of the variations in financial performance, highlighting the limited but impactful role of short-term debt in the capital structure. The study shows the need for manufacturing firms to optimize their financing strategies by prioritizing internal funds before resorting to external short-term debt. Recommendations include exploring alternative investment options, diversifying funding sources, and conducting similar studies across other sectors to validate these findings. This research contributes to the ongoing discourse on capital structure management in developing economies, providing insights for policymakers, investors, and corporate managers.

Rethinking the effect of salinity on nitrogen removal capacity of aerobic granular sludge from the perspective of size distribution and granular morphology.

Granular size induces the operation performance variation of aerobic granular sludge reactor, but the profound reasons are unrevealed. This study investigated the influence of granular size distribution on the reactor operation under salt stress. The effective nitrogen removal was achieved at ≤4% salinity, but declined at 6% salinity. The phenomenon was determined by the granular size fraction. The small granules (d=200-600μm) fraction was 77%-81% at ≤4% salinity, while only 57.32% at 6% salinity. That was positively correlated with nitrite reductase (NIR) activity significantly (p<0.01). Moreover, small granules exhibited smooth surface at ≤4% salinity. The efficient mass transfer area of granules was enlarged by the smooth surface, accelerating substrates mass transfer. Consequently, ammonia monooxygenase (AMO) activity was enhanced significantly (p<0.05). Ammonia-oxidation bacteria, Nitrosomonas and nitrite-reduction bacteria, Paracoccus were dominated in small granules at 4% salinity, while loss at 6% salinity. Overall, small granules with smooth surface favored the enrichment of nitrogen removal microbes via substrate transfer enhancement, and improved the activity of AMO and NIR. Thus, the favorable nitrogen removal performance of aerobic granular sludge reactor was achieved at ≤4% salinity.

The vague language use scale: Clinical utility and psychometrics from adults with traumatic brain injury.

Pragmatic communication difficulties encompass many distinct behaviours, including the use of vague and/or insufficient language, a common characteristic following traumatic brain injury (TBI) that negatively impacts psychosocial outcomes. Existing assessments evaluate pragmatic communication broadly, often with only one or two items capturing each behaviour, thus limiting sensitivity and precision to variations within each behaviour. Given that greater nuance is needed to detect subtle pragmatic communication differences and investigate underlying cognitive mechanisms, a more refined measure is critical to improve psychosocial outcomes. The Vague scale was developed to address those needs. To provide preliminary evidence supporting the novel Vague language use (Vague) scale's reliability, validity and clinical utility. The Vague scale rates each discourse sample utterance for vague language use on a 3-point scale; the measure's Vague score represents the mean of utterance-level ratings. Using the Vague scale, two raters naïve to diagnosis evaluated Cinderella narratives of 46 adults with severe TBI and 46 controls with no brain injury, providing reliability, construct validity and classification accuracy evidence. Vague scores were also compared to other clinical measures to gather criterion-related validity evidence. Interrater agreement across all transcripts was moderate. Construct validity was supported by expected group differences and criterion validation, including significant relationships with increased violations of Grice's maxim of quantity and measures of lexical variation; significant relationships with psychosocial outcomes, supporting clinical utility; and nonsignificant relationships with measures of syntax and overall pragmatic communication. Classification accuracy expectedly did not support using Vague scores in isolation for diagnosis, due to unacceptable sensitivity (0.696). Evidence supported the Vague scores' psychometric properties. Thus, the Vague scale shows promise as a measure of one distinct pragmatic communication behaviour: vague language use. Future research should apply the Vague scale to determine its sensitivity in individuals with subtle social communication challenges (e.g., mild TBI), explore its utility with more naturalistic discourse samples as part of a pragmatic communication battery, longitudinally examine changes in Vague scores, and investigate cognitive mechanisms underlying this specific pragmatic communication behaviour. What is already known on this subject Use of vague language is common following traumatic brain injury (TBI) and may contribute to negative psychosocial outcomes related to employment and relationships. However, existing measures of vague language lack sensitivity and precision, limiting their utility for identifying subtle performance variations or determining the cognitive mechanisms underlying this specific pragmatic communication behaviour. What this study adds to existing knowledge The current study gathered promising reliability, validity and clinical utility evidence to support using the novel Vague language use (Vague) scale, which was developed to address these limitations. Based on complex (Cinderella) stories of adults with and without TBI, Vague scores demonstrated moderate interrater agreement and promising construct validity based on expected group differences and criterion validation, including moderate associations with related constructs and weak associations with unrelated constructs. Because pragmatic communication profiles post-TBI can vary, classification accuracy expectedly indicated that Vague scores should not be used alone to identify communication differences post-TBI. What are the clinical implications of this work? Vague scores show promise for documenting clients' use of vague language and planning intervention to address associated discourse-level challenges. Future research should investigate applying the Vague scale to naturalistic discourse samples (1) as part of a battery that sensitively and precisely identifies pragmatic communication differences and (2) as a tool for investigating cognitive mechanisms underlying vague language use, with the goal of improving interventions that support pragmatic communication and enhance psychosocial outcomes.

CLASSIFICATION OF GREEN BUILDING TECHNIQUES APPLICABLE TO THE FEDERAL CAPITAL CITY, ABUJA NIGERIA

This study applied a Descriptive-Survey Research Design with a mixed-method approach to assess the socio-economic and environmental impacts of green building techniques in Abuja, Nigeria. Data were gathered from primary and secondary sources, including structured surveys, semi-structured interviews, field observations, and literature reviews. A multi-stage sampling method identified key stakeholders such as developers, architects, government officials, and property owners, using the Krejcie and Morgan sample size determination table for statistical accuracy. Quantitative data centered on financial metrics, cost analysis, and stakeholders' perceptions, while qualitative data provided insights through interviews and direct observations. Data analysis incorporated statistical methods, AMOS (Structural Equation Modeling), comparative analysis, and content analysis to evaluate sustainability indicators, economic viability, and policy frameworks. The study classified green building techniques in Abuja, focusing on five categories: Energy-Saving and Energy Utilization (ESEU), Water-Saving and Water Utilization (WSWU), Material-Saving and Material Utilization (MSMU), Indoor Environmental Quality (IEQ), and Site Planning and Land Surveying (SPLS). The findings highlighted the varying performance of 19 techniques in the ESEU category, with Off-Grid Systems (OSG) achieving an average performance of 37.8% and Traditional Grid Systems (TTSG) achieving higher performance levels in most techniques. In the WSWU category, several techniques like WSWU-2, WSWU-3, and WSWU-4 exhibited high performance, with a 100% adoption in TTSG. In the MSMU category, techniques like MSMU-9 and MSMU-10 achieved near-perfect performance in both OSG and TTSG, while others, such as MSMU-13, showed limited adoption. The IEQ category displayed a continuous variation in performance, with significant improvements in TTSG for techniques like IEQ-7 and IEQ-14, which recorded increases of 23.0% and 19.3%, respectively. Finally, in the SPLS category, the performance of techniques such as SPLS-17 and SPLS-26 was exemplary, with full implementation observed. The statistical analysis, including comparisons between OSG and TTSG systems, demonstrated that green building practices could significantly enhance energy efficiency, water conservation, and material utilization. However, challenges such as the limited adoption of renewable materials, inconsistent implementation of water-saving technologies, and inadequate policy frameworks were identified. The findings underline the need for policy improvements, capacity building, and greater public awareness to accelerate the widespread adoption of green building techniques in Abuja. The study’s statistical findings were supported by a Cronbach's alpha of 0.943, indicating high reliability in the research instruments.

Impact of Electrical Properties Variations of Human-Body Phantom on Implantable Antenna Performance During In-Vitro Measurement

The Implantable Medical Antenna (IMA) is extensively used for continuous patient health monitoring. For in-vitro testing of IMA, the development of human-body-phantom is a necessary task before implantation within the torso. The phantom can be developed by mixing different chemicals. Evaporation from liquid phantom and bacterial activities in semi-solid phantom during in-vitro measurement can change the electrical properties (relative permittivity and conductivity) of the phantom model which may lead to variation in implantable antenna performance. From a realistic point of view, the overall permittivity and conductivity of the human body can change due to variations in water content, blood properties, collagen content, hormones, development of diseases especially cancer, Madelung’s disease, etc. Therefore, it is required to have knowledge about the dependence of IMA performance on equivalent electrical properties of homogeneous body phantom which has been studied in this article. From this study, it is observed using a curve-fitting technique that mathematical formulation between IMA parameters and variable effective permittivity and conductivity of equivalent body model are difficult. That’s why; an Artificial Neural Network (ANN) has been developed here for proper estimation considering only ∼1% and 1.5% errors with respect to the simulated and measured responses, respectively.