Work Environment Scale

The Work Environment Scale (WES) comprehensively measures 10 dimensions of the workplace social and organizational environment: involvement, peer cohesion, supervisor support, autonomy, task orientation, work pressure, clarity, control, innovation, and physical comfort. Developed by Moos and colleagues, the WES captures how the organizational climate—the shared perceptions of and attitudes about the work setting—influences worker wellbeing, satisfaction, and performance. The scale is widely used for organizational assessment, team diagnosis, and evaluation of workplace interventions.

Moos, R. H. (1994). Work Environment Scale manual (2nd ed.). Consulting Psychologists Press.

Insel, P. M., & Moos, R. H. (1994). Work, family, and the evaluation of being in a social environment. J Community Psychol, 22(3), 195–208.


Work-Life Balance Scale

The Work-Life Balance Scale (WLBS) is an 18-item instrument measuring the degree of conflict and enrichment between work and non-work life domains. Developed by Carlson, Kacmar, and Williams in 2000, the WLBS assesses three dimensions of work-family conflict (time-based, strain-based, behavior-based) and their inverse relationship to work-family enrichment.

Carlson, D. S., Kacmar, K. M., & Williams, L. J. (2000). Construction and initial validation of a multidimensional measure of work-family conflict. Journal of Vocational Behavior, 56(3), 249-276.

Fisher, G. G., Bulger, C. A., & Smith, C. S. (2009). Beyond work and family: A measure of work/non-work interference and enhancement. Journal of Occupational Health Psychology, 14(4), 441-456.


Work-Related Burnout Scale

Christina Maslach, Susan E. Jackson, Wilmar Schaufeli

The Work-Related Burnout Scale, most commonly embodied in the Maslach Burnout Inventory (MBI) developed by Christina Maslach and Susan Jackson in 1986, is the most widely used instrument for assessing occupational burnout. The MBI measures three core dimensions of burnout: emotional exhaustion (depletion of emotional resources), depersonalization (cynical, detached attitude toward work and others), and reduced personal accomplishment (diminished sense of effectiveness and achievement). The MBI has been translated into numerous languages and is considered the gold standard in burnout research and occupational health assessment.

Maslach, C., & Jackson, S. E. (1986). Maslach Burnout Inventory Manual (2nd ed.). Palo Alto, CA: Consulting Psychologists Press.

Schaufeli, W. B., Leiter, M. P., Maslach, C., & Jackson, S. E. (1996). MBI-GS: Maslach Burnout Inventory-General Survey. Palo Alto, CA: Consulting Psychologists Press.

copenhagen-burnout-inventory oldenburg-burnout-inventory effort-reward-imbalance-scale areas-of-worklife-scale recovery-experience-questionnaire


Working Alliance Inventory

The Working Alliance Inventory (WAI) is a validated, empirically supported measure of the therapeutic alliance—the collaborative relationship between therapist and client. Developed by Horvath and Greenberg in 1989, the WAI operationalizes Bordin's tripartite model of alliance: agreement on goals, agreement on tasks, and emotional bond. It is one of the most widely used alliance measures in psychotherapy research and is a strong predictor of psychotherapy outcome across diverse theoretical orientations and client populations.

Horvath, A. O., & Greenberg, L. S. (1989). Development and validation of the Working Alliance Inventory. Journal of Counseling Psychology, 36(2), 223–233.

session-rating-scale outcome-rating-scale therapeutic-alliance-scale therapeutic-alliance-scale collaborative-study-psychotherapy


Workload Profile

The Workload Profile (WP), developed by Pamela Tsang and Veronica Velazquez in 1996, is a multidimensional subjective workload assessment tool that refines the NASA Task Load Index by allowing respondents to assign relative importance weights to workload dimensions dynamically, rather than through separate pairwise comparisons. The WP divides the 0-100 point workload scale into segments corresponding to distinct cognitive and attentional demands, enabling respondents to visually allocate load across dimensions and thereby create a profile that reflects the task-specific pattern of burden.

Tsang, P. S., & Velazquez, V. L. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358–381.

nasa-task-load-index cognitive-load-scale situational-awareness-rating operator-performance-scale


Negative Acts Questionnaire

NAQ
Workplace Bullying Scale
Einarsen Raknes Scale

The Negative Acts Questionnaire (NAQ) measures exposure to workplace bullying and harassment—persistent negative social interactions including exclusion, denigration, and intimidation. Developed by Einarsen and colleagues in 1994, the 22-item scale captures a range of harmful workplace behaviors. Bullying exposure correlates strongly with psychological distress, health problems, absenteeism, and turnover, making the NAQ valuable in occupational health and organizational assessment.

Einarsen, S., Raknes, B. I., Matthiesen, S. B., & Hellesøy, O. H. (1994). Bullying and harassment at work: Relationships to work environment quality. European Journal of Work and Organizational Psychology, 4(2), 215–226.

Notelaers, G., & Einarsen, S. (2013). The world we know and the world we do not know about workplace bullying. In S. Einarsen, H. Hoel, D. Zapf, & C. L. Cooper (Eds.), Bullying and harassment in the workplace: Developments in theory, research, and practice (pp. 75–93). CRC Press.

Lutgen-Sandvik, P., Tracy, S. J., & Alberts, J. K. (2007). Burned by bullying in the American workplace: Prevalence, perception, degree, and impact. Journal of Management Studies, 44(6), 837–862.

occupational-stress-index perceived-organizational-support leader-member-exchange-scale psychological-capital-questionnaire job-descriptive-index


Workplace Incivility Scale

Negative Acts Questionnaire (NAQ) - adapted

Workplace social climate and mistreatment

Lilia M. Cortina, Vicki J. Magley, Janet H. Williams, Regina D. Langhout; based on incivility concept by Andersson & Pearson

The Workplace Incivility Scale (WIS) is an assessment tool measuring exposure to low-intensity interpersonal mistreatment in occupational settings. Based on the concept of 'incivility' developed by Andersson and Pearson, and operationalized by Cortina and colleagues in 2001, the WIS captures rude, condescending, and hostile communication, excluding the overt aggression characteristic of workplace bullying or harassment. Workplace incivility is increasingly recognized as a significant occupational health risk with consequences for employee wellbeing, productivity, and organizational culture.

Andersson, L. M., & Pearson, C. M. (1999). Tit for tat? The spiraling effect of incivility in the workplace. Academy of Management Review, 24(3), 452-471.

Cortina, L. M., Magley, V. J., Williams, J. H., & Langhout, R. D. (2001). Incivility in the workplace: Incidence and impact. Journal of Occupational Health Psychology, 6(1), 64-80.

copenhagen-burnout-inventory areas-of-worklife-scale recovery-experience-questionnaire effort-reward-imbalance-scale presenteeism-scale


Workplace Ostracism Scale

The Workplace Ostracism Scale measures the extent to which an employee feels excluded, ignored, or dismissed by colleagues and supervisors—a form of social exclusion distinct from harassment but equally harmful to mental health and performance. Developed by Ferris, Brown, Berry, and Lian, the WOS captures subtle exclusionary behaviors: being left out of conversations, having contributions ignored, or being given the silent treatment. Workplace ostracism predicts depression, anxiety, reduced engagement, and turnover, making it critical for identifying and addressing subtle organizational toxicity.

Ferris, D. L., Brown, D. J., Berry, J. W., & Lian, H. (2008). The development and validation of the Workplace Ostracism Scale. J Appl Psychol, 93(6), 1348–1366.

Williams, K. C. (2001). Ostracism: The power of silence. Guilford Press.


Workplace Violence Scale

The Workplace Violence Scale measures employee exposure to physical and verbal violence, threats, and harassment in occupational settings. Developed by the International Labour Organization, it captures the prevalence and severity of violent incidents affecting worker safety and health across sectors including healthcare, education, retail, and social services. The scale is essential for identifying organizational violence risk and monitoring workplace safety interventions.

Chappell, D., & Di Martino, V. (2006). Violence at work (3rd ed.). International Labour Office.

Orrenius, M. K., & Chappell, N. L. (2002). The institutional and social context of violence in nursing homes. J Health Soc Behav, 43(2), 188–203.


WFNS Scale

World Federation of Neurosurgical Societies Scale for Subarachnoid Hemorrhage

Subarachnoid hemorrhage severity classification

Drake and World Federation of Neurosurgical Societies Committee

The WFNS Scale is a standardized grading system for assessing severity and prognosis in subarachnoid hemorrhage (SAH) published by the World Federation of Neurosurgical Societies in 1988. The five-point scale combines the Glasgow Coma Scale (GCS) with presence of motor deficit to classify SAH severity. The WFNS Scale is more objective than the earlier Hunt-Hess Scale and is increasingly preferred in contemporary neurosurgical practice, particularly in Europe and internationally.

Drake, C. G. (1988). Report of the World Federation of Neurosurgical Societies Committee on a universal subarachnoid hemorrhage grading scale. Journal of Neurosurgery, 68(6), 985-986.

hunt-hess-scale nihss updrs edss-multiple-sclerosis


Bates-Jensen Wound Assessment Tool

Bates-Jensen Wound Assessment Tool for Pressure Ulcer Evaluation

BJWAT
Bates-Jensen Assessment Tool
Pressure Ulcer Scale for Healing

The Bates-Jensen Wound Assessment Tool (BJWAT), originally developed as the Pressure Sore Status Tool, is a comprehensive instrument for objectively assessing pressure ulcer characteristics and monitoring healing progress. Created by Barbara M. Bates-Jensen, the tool evaluates 13 distinct wound dimensions including size, depth, tissue type, and exudate. It provides quantitative assessment of wound severity and is useful for tracking changes over time and evaluating treatment effectiveness.

Bates-Jensen, B. M. (1997). The Pressure Sore Status Tool: an outcome measure for pressure sores. Journal of Gerontological Nursing, 23(5), 20-28.

Bates-Jensen, B. M., Vredevoe, D. L., & Brecht, M. L. (2001). Diffuse reflectance spectrophotometry: A potential tool for detecting pressure ulcer risk on darker skin. Advances in Skin and Wound Care, 14(3), 141-147.

braden-scale wound-assessment-bates-jensen nursing-sensitive-indicators care-dependency-scale


WPM

WPM (Weighted Product Model) is a ranking multi-criteria decision-making (MCDM) method introduced by Miller, D. W., Starr, M. K. in 1969. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Miller, D. W., Starr, M. K. (1969). Executive Decisions and Operations Research. Prentice-Hall

ahp anp bwm bwm-bayesian ccsd cilos cimas critic


WRF Model

Weather Research and Forecasting
WRF
ARW
NMM

The Weather Research and Forecasting (WRF) model is a mesoscale atmospheric simulation system used for weather forecasting, research, and climate applications. Developed cooperatively by NCAR, NOAA, and academic institutions, WRF became operational in 2004 and has become one of the most widely used atmospheric models worldwide.

Skamarock, W. C., Klemp, J. B., Dudhia, J., et al. (2008). A Description of the Advanced Research WRF Version 3. NCAR Technical Note NCAR/TN-475+STR.

Powers, J. G., Klemp, J. B., Skamarock, W. C., et al. (2017). The weather research and forecasting model: Overview, system efforts, and future directions. Bulletin of the American Meteorological Society, 98(8), 1717-1737.

hysplit bulk-aerodynamic-flux eddy-covariance monin-obukhov-similarity


Writing Apprehension Test

The Writing Apprehension Test measures the degree of anxiety and negative affect experienced in writing situations. Developed by Daly and Miller in 1975, the WAT identifies students with writing anxiety—a prevalent barrier to academic success, particularly in college coursework where writing is extensive. Writing apprehension leads to avoidance of writing tasks, procrastination, and reduced writing quality independent of actual writing ability. Early identification and targeted support can significantly improve both writing confidence and academic outcomes.

Daly, J. A., & Miller, M. D. (1975). The empirical development of an instrument to measure writing apprehension. Research in the Teaching of English, 9(3), 242–249.

Choi, H. J. (2011). Writing apprehension, attitude toward writing and self-efficacy in basic college writers. Journal of Korea Academy Industrial Cooperation Society, 12(5), 2023–2031.

test-anxiety-inventory academic-resilience-scale procrastination-assessment-scale academic-help-seeking-scale study-skills-assessment


WSM

WSM (Weighted Sum Model (Simple Additive Weighting)) is a ranking multi-criteria decision-making (MCDM) method introduced by Fishburn, P. C. in 1967. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Fishburn, P. C. (1967). Additive utilities with incomplete product sets: Application to priorities and assignments. Operations Research


X-Ray Crystallography

X-ray diffraction
crystallography
single-crystal X-ray

William Henry Bragg & William Lawrence Bragg

X-ray crystallography is a technique that determines the three-dimensional atomic structure of crystals by analyzing the diffraction patterns produced when X-rays pass through them. Developed by William Henry Bragg and William Lawrence Bragg in 1912, X-ray crystallography has become the gold standard for structure determination in chemistry, biochemistry, and materials science, winning multiple Nobel Prizes for its profound impact.

Bragg, W. H., & Bragg, W. L. (1913). The reflection of X-rays by crystals. Proceedings of the Royal Society of London, 88(605), 428–438.

Rhodes, G. (2006). Crystallography Made Crystal Clear: A Guide for Users of Macromolecular Models (3rd ed.). Academic Press.


X-ray Densitometry

X-ray Densitometry for Wood Density Measurement

X-ray densitometry is a nondestructive method for measuring wood density, microdensity profiles, and ring-by-ring density variation in wood samples using X-ray image analysis. The method uses attenuation of X-rays passing through wood to quantify mass per unit volume. It enables rapid assessment of wood quality without destroying material, making it valuable for research, timber grading, and genetic selection programs.

Hansmann, C., Wimmer, R., & Gindl, W. (2007). Assessing damage in wood-polymer composites by depth-sensing indentation. Composites Part A, 38(6), 1502–1508.

Moya, R., Rodríguez-Zuñiga, A., & Valerio, A. (2021). Relationship between near-infrared wood density and structural properties of Tectona grandis and Gmelina arborea. Holzforschung, 75(1), 94–101.


X-ray Photoelectron Spectroscopy

electron spectroscopy for chemical analysis

X-ray Photoelectron Spectroscopy (XPS), also known as Electron Spectroscopy for Chemical Analysis (ESCA), is a surface-sensitive analytical technique that measures the kinetic energies of photoelectrons ejected from a material by high-energy X-rays. Developed by Kai Siegbahn in 1967, XPS determines elemental composition, chemical oxidation states, and chemical bonding within ~10 nanometers of a surface. It is indispensable in materials science for surface characterization, corrosion studies, oxide analysis, and interface chemistry.

Siegbahn, K., Nordling, C., Fahlman, A., et al. (1967). ESCA: Atomic, Molecular and Solid State Structure Studied by Means of Electron Spectroscopy. Almqvist and Wiksells.

Briggs, D., & Seah, M. P. (2003). Practical Surface Analysis by Auger and X-ray Photoelectron Spectroscopy (2nd ed.). John Wiley & Sons.

Moulder, J. F., Stickle, W. F., Sobol, P. E., & Bomben, K. D. (1992). Handbook of X-ray Photoelectron Spectroscopy. Physical Electronics.


X-13ARIMA-SEATS is the standard seasonal adjustment program produced by the U.S. Census Bureau, combining RegARIMA pre-adjustment with either the classical X-11 filter or the model-based SEATS signal-extraction algorithm. It is the official tool used by national statistical agencies worldwide — including Eurostat and the U.S. Bureau of Labor Statistics — to remove recurring calendar and seasonal patterns from monthly or quarterly economic time series such as GDP, employment, and retail sales.

X-13ARIMA-SEATS (U.S. Census Bureau, free)

Output: Seasonally adjusted series, trend-cycle, irregular component

Findley, D. F., Monsell, B. C., Bell, W. R., Otto, M. C., & Chen, B.-C. (1998). New capabilities and methods of the X-12-ARIMA seasonal adjustment program. Journal of Business & Economic Statistics, 16(2), 127–152.


XANES

XANES spectroscopy
near-edge X-ray absorption

X-ray Absorption Near Edge Structure (XANES) is a synchrotron X-ray spectroscopy technique that measures the electronic and geometric structure around a specific atom by analyzing the X-ray absorption spectrum within about 50 eV of an absorption edge. Developed by Lee and Pendry in 1975, XANES is complementary to EXAFS and reveals valence state, local symmetry, and unoccupied orbital structure through near-threshold features and resonances.

Lee, P. A., & Pendry, J. B. (1975). Theory of extended x-ray absorption fine structure. Physical Review B, 11(8), 2795-2811.

Koningsberger, D. C., & Prins, R. (Eds.). (1988). X-ray Absorption: Principles, Applications, Techniques of EXAFS, SEXAFS, and XANES. John Wiley & Sons.


Xenophobia Scale

Xenophobia and Anti-Foreign Sentiment Assessment Scale

Alin Ceobanu, Xavier Escandell, Elke Schlueter

The Xenophobia Scale measures fear, discomfort, or prejudice toward foreign nationals and immigrants. Unlike immigration policy preferences (which can reflect economic or pragmatic considerations), xenophobia captures affective and attitudinal dimensions—emotional threat perception, negative stereotypes, and cultural distance. Developed by migration scholars including Ceobanu and Escandell, it is essential for understanding antiforeign sentiment and discriminatory attitudes across diverse contexts.

Ceobanu, A. M., & Escandell, X. (2010). Comparative analyses of public attitudes toward immigrants and immigration using multinational survey data: The European Social Survey. Journal of Ethnic and Migration Studies, 36(6), 953-969.

Lahav, B., & Coursey, M. (2012). When the foreign direct investment FDI becomes a security issue: Russia, China, the United States, and the Middle East. Brookings Institution Press.

Schlueter, E. (2016). The causes and consequences of xenophobia. Proceedings of the National Academy of Sciences, 113(47), 13368-13373.

intergroup-contact-scale generalized-trust-scale democratic-values-scale institutional-trust-scale social-cohesion-scale


XI

The Xerostomia Inventory (XI) is an 11-item self-report questionnaire designed to measure subjective perception of dry mouth (xerostomia). Developed by Thomson and colleagues in 1999, it has become the standard validated instrument for assessing dry mouth severity in clinical practice and research. The XI captures both the frequency and severity of oral dryness symptoms and their impact on daily functioning, distinguishing symptomatic xerostomia from objective salivary gland dysfunction.

Thomson, W. M., Chalmers, J. M., Spencer, A. J., & Williams, S. M. (1999). The xerostomia inventory: A multi-item approach to measuring dry mouth. Community Dentistry and Oral Epidemiology, 27(6), 406-412.


XGBoost

XGBoost
extreme gradient boosting
scalable tree boosting

XGBoost (Extreme Gradient Boosting) is a scalable tree-boosting algorithm introduced by Tianqi Chen and Carlos Guestrin in 2016. It builds a strong predictor by adding decision trees one at a time, each correcting the errors left by the trees before it, and is a powerful prediction method widely used in competitions.

Ensemble (gradient-boosted decision trees)

Chen, T. & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD, 785–794.

gradient-boosting random-forest decision-tree svm-classification logistic-regression


XRD Rietveld Refinement

Rietveld refinement
powder diffraction refinement

XRD Rietveld Refinement is a method for extracting detailed crystal structure information from powder diffraction data by comparing observed and calculated diffraction patterns through least-squares refinement. Developed by Hugo Rietveld in 1969, this technique enables determination of atomic positions, occupancies, thermal parameters, and phase fractions directly from powder data without requiring single crystals. It is the standard approach in materials characterization for structural analysis, phase identification, and quantification.

Rietveld, H. M. (1969). A profile refinement method for nuclear and magnetic structures. Journal of Applied Crystallography, 2(2), 65-71.

Young, R. A. (Ed.). (1993). The Rietveld Method. Oxford University Press/International Union of Crystallography.

Rodriguez-Carvajal, J. (2004). Recent advances in magnetic structure determination by neutron powder diffraction. Physica B, 192(1-2), 55-69.


Yale-Brown Obsessive Compulsive Scale

Yale-Brown Obsessive Compulsive Scale (Y-BOCS)

The Y-BOCS is a 10-item clinician-administered scale designed to assess the severity of obsessive-compulsive disorder (OCD) symptoms in adolescents and adults. Developed by Goodman and colleagues in 1989, it has become the gold standard severity measure and primary outcome tool in OCD research and clinical trials. The scale is widely used in psychiatric settings to track symptom burden over time and evaluate treatment response.

Goodman, W. K., Price, L. H., Rasmussen, S. A., Mazure, C., Fleischmann, R. L., Hill, C. L., ... & Charney, D. S. (1989). The Yale-Brown Obsessive Compulsive Scale: I. Development, use, and reliability. Archives of General Psychiatry, 46(11), 1006–1011.

Goodman, W. K., Price, L. H., Rasmussen, S. A., Mazure, C., Fleischmann, R. L., Hill, C. L., ... & Charney, D. S. (1989). The Yale-Brown Obsessive Compulsive Scale: II. Validity. Archives of General Psychiatry, 46(11), 1012–1016.

Scahill, L., Riddle, M. A., McSwiggin-Hardin, M., Ort, S. I., King, R. A., Goodman, W. K., ... & Leckman, J. F. (1997). Children's Yale-Brown Obsessive Compulsive Scale: Reliability and validity. Journal of the American Academy of Child & Adolescent Psychiatry, 36(6), 844–853.


Lawrence Scahill, Mark Riddle, W. Goodman (Y-BOCS)

The Children's Yale-Brown Obsessive Compulsive Scale (CY-BOCS) is a 10-item clinician-administered semi-structured interview for assessing obsessive-compulsive symptoms in children and adolescents ages 6–17 years. Developed by Scahill, Riddle, and colleagues in 1997 as a child adaptation of the adult Y-BOCS, the CY-BOCS quantifies severity of obsessions and compulsions, insight, resistance, and functional impact. It is the gold-standard outcome measure in pediatric OCD research and clinical practice for diagnosis, severity rating, and treatment monitoring.

Scahill, L., Riddle, M. A., McSwiggin-Hardin, M., Ort, S. I., King, R. A., Goodman, W. K., . . . Leckman, J. F. (1997). Children's Yale-Brown Obsessive Compulsive Scale: Reliability and validity. Journal of the American Academy of Child & Adolescent Psychiatry, 36(6), 844–853.

Goodman, W. K., Price, L. H., Rasmussen, S. A., Mazure, C., Fleischmann, R. L., Hill, C. L., . . . Charney, D. S. (1989). The Yale-Brown Obsessive Compulsive Scale: Development, use, and reliability. Archives of General Psychiatry, 46(11), 1006–1011.


YFAS

YFAS 2.0
Yale Food Addiction Scale Revised

Ashley Gearhardt, William Corbin, Kelly Brownell

The YFAS is a self-report questionnaire measuring symptoms of addictive-like eating behaviour in response to highly palatable foods. Developed by Gearhardt, Corbin, and Brownell in 2009, it is based on diagnostic criteria for substance use disorder and adapted to assess dependence-like symptoms related to food consumption. The YFAS 2.0, released in 2016, improved psychometric properties and reduced item burden. It is used in research on obesity, food addiction, and eating behaviour regulation.

Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2009). Preliminary validation of the Yale Food Addiction Scale. Appetite, 52(2), 430–436.

Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2016). Development of the Yale Food Addiction Scale Version 2.0. European Eating Disorders Review, 24(3), 218–225.

Schulte, E. M., Avena, N. M., & Gearhardt, A. N. (2018). Which foods may be addictive? The roles of processing, fat content, and glycemic load. Nutrients, 7(12), 5541.

binge-eating-scale yale-food-addiction-scale three-factor-eating-questionnaire ede-q


Yield Line Theory

Yield Line Theory for Reinforced Concrete Slabs

yield-line analysis
yield-line method
Johansen yield-line method
plastic slab analysis

Plastic limit analysis of plates and slabs

1943 (doctoral thesis, Danish); 1962 (English translation)

Yield Line Theory is a plastic limit-analysis method used in structural civil engineering to determine the ultimate load-carrying capacity of reinforced concrete slabs. Developed by K. W. Johansen in the 1940s, it assumes that at failure the slab subdivides into rigid regions separated by lines of intense plastic rotation — called yield lines — where the reinforcement has fully yielded. The approach gives the collapse load directly and is widely used in slab design and assessment.

Structural analysis method (plasticity-based)

Geometric slab dimensions, reinforcement layout, material strengths (yield moments)

Johansen, K. W. (1962). Yield-Line Theory. Cement and Concrete Association, London.

Wood, R. H. (1961). Plastic and Elastic Design of Slabs and Plates. Thames and Hudson, London.

finite-element-method limit-analysis strut-and-tie-model punching-shear-analysis hillerborg-strip-method plastic-hinge-analysis


Yoga Self-Efficacy Scale

Mind-body self-efficacy and practice sustainability

Based on Bandura's self-efficacy theory; adapted for yoga practice

The YSES measures an individual's confidence and perceived ability to successfully perform yoga practice, overcome barriers, and sustain a regular yoga routine. Grounded in Bandura's self-efficacy theory, it predicts adherence to yoga programs and likelihood of realizing health benefits in clinical and community populations.

Self-report efficacy and confidence scale

Cramer, H., Hall, H., & Leach, M. J. (2016). Systematic review and meta-analysis of yoga for low back pain: A 2016 update. Spine Journal, 16(12), 1547–1557.

Goleman, D., & Davidson, R. J. (2017). Altered traits: Science reveals how meditation changes your mind and brain. New York: Bantam.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.

nature-relatedness-scale music-therapy-assessment-tool holistic-caring-inventory spiritual-care-competence-scale


YOLO

YOLO: You Only Look Once — Unified, Real-Time Object Detection

You Only Look Once
YOLO detector
YOLOv1
single-shot detector
real-time object detection

Redmon, J.; Divvala, S.; Girshick, R.; Farhadi, A.

YOLO (You Only Look Once) is a single-shot, end-to-end convolutional object detector introduced by Redmon, Divvala, Girshick, and Farhadi at CVPR 2016. It reframes object detection as a single regression problem — predicting bounding box coordinates and class probabilities directly from an image in one forward pass — achieving real-time detection speeds that prior two-stage methods such as R-CNN could not match. The original paper spawned a widely adopted family of successors (YOLOv2 through v11) that continues to dominate applied object detection benchmarks.

Single-shot convolutional object detector

Object detection (localization + classification)

Custom 24-layer CNN (GoogLeNet-inspired)

S×S grid, B bounding boxes, C class probabilities

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

faster-rcnn ssd-object-detection resnet convolutional-neural-network feature-pyramid-network


Youdens J Statistic

Youden Index
Sensitivity + Specificity - 1

Youdens J statistic, also called the Youden index, measures the maximum difference between the true positive rate and false positive rate across different classification thresholds. It is useful for selecting optimal cutoff points in diagnostic testing.

Youden, W. J. (1950). Index for rating diagnostic tests. Cancer, 3(1), 32-35.

Perkins, N. J., & Schisterman, E. F. (2006). The inconsistency of optimal cutpoints obtained using two criteria based on the receiver operating characteristic curve. American Journal of Epidemiology, 163(7), 670-675.

sensitivity specificity balanced-accuracy f1-score roc-auc


Z-AHP

Z-AHP (Z-Number Analytic Hierarchy Process) is a weighting multi-criteria decision-making (MCDM) method introduced by Mahammad Nuriyev (Khazar University, Baku, Azerbaijan) in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Hierarchical pairwise comparison weighting under Z-number uncertainty

Nuriyev, M. (2020). Z-numbers Based Hybrid MCDM Approach for Energy Resources Ranking and Selection. International Journal of Energy Economics and Policy

z-topsis z-promethee z-marcos z-waspas z-edas z-vikor z-copras topsis


Z-BWM

Z-BWM (Z-Number Best-Worst Method) is a weighting multi-criteria decision-making (MCDM) method introduced by Aboutorab, Saberi, Asadabadi, Hussain, Chang (UTS Sydney, Australia) in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Pairwise comparison weighting under Z-number uncertainty

Aboutorab, H., Saberi, M., Asadabadi, M.R., Hussain, O., Chang, E. (2018). ZBWM: The Z-number extension of Best Worst Method and its application for supplier development. Expert Systems with Applications

z-topsis z-marcos z-waspas z-edas z-vikor z-copras topsis marcos


Z-COPRAS

Z-COPRAS (Z-Number extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Zadeh, L. A. in 2011. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Z-Number outranking/ranking — Z-Number (Z = (A, B): restriction A, reliability B; both fuzzy)

Zadeh, L. A. (2011). A note on Z-numbers. Information Sciences


Z-EDAS

Z-EDAS (Z-Number extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Zadeh, L. A. in 2011. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.


Z-MARCOS

Z-MARCOS (Z-Number extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yazdani, M., Pamucar, D., Chatterjee, P., Torkayesh, A. E. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Yazdani, M., Pamucar, D., Chatterjee, P., Torkayesh, A. E. (2021). A multi-tier sustainable food supplier selection model under uncertainty (MARCOS-D / Z-MARCOS adaptation). Operations Management Research


Z-PROMETHEE

Z-PROMETHEE (Z-Number Preference Ranking Organization Method (II)) is a ranking multi-criteria decision-making (MCDM) method introduced by Mahammad Nuriyev (Khazar University, Baku, Azerbaijan); builds on Brans-Vincke 1985 PROMETHEE in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Outranking method with Z-number uncertainty (PROMETHEE II — full ranking)

z-ahp z-bwm ahp bwm entropy critic merec swara


Z-scan

Z-scan method
nonlinear refraction measurement

Mansoor Sheik-Bahae, David Hagan, and Eric Van Stryland

The Z-scan technique is an experimental method for measuring nonlinear optical properties of materials, particularly third-order susceptibility and nonlinear absorption. Developed by Sheik-Bahae, Hagan, and Van Stryland in 1990, Z-scan uses a tightly focused laser beam and moves the sample along the beam propagation axis (z-axis), recording transmission variation to deduce nonlinear refraction and absorption coefficients with high sensitivity.

Sheik-Bahae, M., Said, A. A., Wei, T. H., Hagan, D. J., & Van Stryland, E. W. (1990). Sensitive measurement of optical nonlinearities using a single beam. IEEE Journal of Quantum Electronics, 26(4), 760-769.

Sheik-Bahae, M., Hutchings, D. C., Hagan, D. J., & Van Stryland, E. W. (1991). Dispersion of bound electronic nonlinear susceptibility in solids. IEEE Journal of Quantum Electronics, 27(6), 1296-1309.

Cohadon, P. F., Briant, C. C., Crozat, P., Conti, C., Bachelot, P., & Antoine, C. (2001). Z-scan technique for characterizing optical properties of materials. Applied Physics Reviews, 98(5), 1755-1768.


Z-SCORE-NORMALIZATION

Z-SCORE-NORMALIZATION (Z-Score Normalization — standardisation to zero mean and unit standard deviation) is a normalization multi-criteria decision-making (MCDM) method introduced by Hellwig, Z. in 1968. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Hellwig, Z. (1968). Zastosowanie metody taksonomicznej do typologicznego podzialu krajow ze wzgledu na poziom ich rozwoju oraz zasoby i strukture wykwalifikowanych kadr technicznych. Przeglad Statystyczny


Z-TOPSIS

Z-TOPSIS (Z-Number extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Gardashova, L. A. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Gardashova, L. A. (2018). Z-Number Based TOPSIS Method in Multi-Criteria Decision Making. Advances in Intelligent Systems and Computing


Z-VIKOR

Z-VIKOR (Z-Number extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Shen, K.-w., Wang, J.-q., Wang, T.-l. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Shen, K.-w., Wang, J.-q., Wang, T.-l. (2018). Z-VIKOR Method Based on a New Comprehensive Weighted Distance Measure of Z-Number and Its Application. IEEE Transactions on Fuzzy Systems


Z-WASPAS

Z-WASPAS (Z-Number extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Ghoushchi, S. J., Yousefi, S., Khazaeili, M. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Ghoushchi, S. J., Yousefi, S., Khazaeili, M. (2021). Theory-Based Failure Modes and Effect Analysis for Medication Errors (Z-SWARA & Z-WASPAS). Journal of Healthcare Engineering


Zarit Caregiver Burden Interview

ZBI
Zarit Burden Interview
Caregiver Burden Scale

The Zarit Caregiver Burden Interview, developed by Steven H. Zarit and colleagues in 1980, is a widely used assessment tool designed to quantify the subjective burden experienced by informal caregivers of persons with dementia or other chronic illnesses. The 22-item instrument measures emotional, financial, and physical strain related to caregiving and has become a standard in geriatric, gerontology, neurology, and behavioral health settings worldwide.

Zarit, S. H., Reever, K. E., & Bach-Peterson, J. (1980). Relatives of the impaired elderly: Correlates of feeling burdened. Gerontologist, 20(6), 649-655.

Zarit, S. H., Anthony, C. R., & Boutselis, M. (1987). Interventions with care givers of dementia patients: Comparison of two approaches. Psychol Aging, 2(1), 9-15.


Zeeman-Doppler Imaging

Zeeman-Doppler Imaging for Stellar Magnetic Field Mapping

ZDI
Doppler Imaging
Magnetic Field Mapping

Zeeman-Doppler imaging is a technique for reconstructing stellar magnetic field maps by combining Doppler broadening of spectral lines with the Zeeman splitting caused by magnetic fields. Pioneered by Jean-Francois Donati in the 1990s, this method reveals how magnetic fields are distributed on stellar surfaces and how they evolve with time.

Donati, J. F., Semel, M., Carter, B. D., Rees, D. E., & Collier Cameron, A. (1997). Spectropolarimetric observations of active stars. Monthly Notices of the Royal Astronomical Society, 291(4), 658-682.

Piskunov, N. E., Wehlau, W. H., & Khokhlova, V. L. (1992). The magnetic field of Alpha-squared Canum Venaticorum. Astronomy & Astrophysics, 267, 583-597.

Reiners, A., Schüssler, M., & Moskowitz, V. (2014). Generalized magnetic reconnection scaling in collisionless asymmetric guide-field reconnection. The Astrophysical Journal, 794(2), 144.


Zero-inflated model

ZIP model
ZINB model
zero-inflated Poisson
zero-inflated negative binomial

A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.

Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.

poisson-regression negative-binomial-regression hurdle-model survival-regression generalized-linear-model robust-poisson-regression


Zero-Inflated Negative Binomial Regression

Zero-Inflated Negative Binomial (ZINB) Regression

Sıfır-Şişirilmiş Negatif Binom Regresyonu (ZINB)

Zero-Inflated Negative Binomial regression is a count model, introduced by Greene (1994), that handles count data showing both an excess of zeros and overdispersion. It combines a binary inflation process that generates structural zeros with a negative binomial count process, making it one of the most widely used distributions for real-world count data.

Greene, W. H. (1994). Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models. NYU Working Paper.

zero-inflated-poisson hurdle-model negative-binomial-regression poisson-regression beta-regression


Zero-Inflated Poisson Regression

Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)

Zero-Inflated Poisson regression is a two-component model for count data that contains more zeros than an ordinary Poisson model can explain. Introduced by Diane Lambert in 1992, it combines a logistic model for the zero-generating mechanism with a Poisson model for the genuine counting process.

Count regression (two-component mixture)

Logit (zero-inflation) + Poisson (count)

Lambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14.

zero-inflated-negative-binomial poisson-regression negative-binomial-regression logistic-regression


Zero-Knowledge Proof

Zero-Knowledge Proof Protocol and Interactive Verification

ZK Proof
Interactive Proof System
Non-interactive ZK Proof

Shafi Goldwasser, Silvio Micali, Charles Rackoff

A zero-knowledge proof is a cryptographic protocol in which a prover can convince a verifier that a statement is true without revealing any additional information beyond the truth of the statement. Introduced by Goldwasser, Micali, and Rackoff in 1985, zero-knowledge proofs have profound applications in authentication, privacy-preserving verification, and blockchain systems.

Cryptographic authentication and verification

Goldwasser, S., Micali, S., & Rackoff, C. (1985). The knowledge complexity of interactive proof systems. SIAM Journal on Computing, 18(1), 186–208.

Ben-Or, M., Goldwasser, S., Kilian, J., & Wigderson, A. (1988). Multi-prover interactive proofs: How to remove intractability assumptions. Proceedings of the 20th ACM STOC, 113–131.

Groth, J. (2016). On the size of pairing-based non-interactive arguments. Advances in Cryptology – EUROCRYPT 2016, 305–326.


Zero-Shot Classification

Sıfır Atışlı Sınıflandırma (Zero-Shot Classification)

Zero-shot classification is a natural-language-processing task that assigns text to categories described in plain language without requiring any labelled training data. Formalised as an entailment problem by Yin, Hay and Roth (2019), it lets a large pretrained language model recognise new categories on the fly simply by naming them, enabling rapid adaptation to fresh label sets.

Natural-language candidate labels via pretrained entailment / language models

Yin, W., Hay, J. & Roth, D. (2019). Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach. EMNLP, 3914-3923.

Brown, T. et al. (2020). Language Models are Few-Shot Learners. NeurIPS.


ZF-CRADIS

ZF-CRADIS (Z-Number Fuzzy Compromise Ranking from Distance to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Puška, A. Božanić, D. Nedeljković, M. Janošević, M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Compromise ranking via distance to ideal/anti-ideal under Z-number uncertainty

Puška, A., Božanić, D., Nedeljković, M., Janošević, M. (2022). Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers–Fuzzy LMAW–Fuzzy CRADIS Model. Axioms

zf-lmaw z-ahp z-bwm fuzzy-ahp fuzzy-bwm entropy critic merec


ZF-LMAW

ZF-LMAW (Z-Number Fuzzy Logarithm Methodology of Additive Weights) is a weighting multi-criteria decision-making (MCDM) method introduced by Puška, A. Božanić, D. Nedeljković, M. Janošević, M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Logarithmic anti-ideal weighting under Z-number uncertainty with group aggregation

zf-cradis z-topsis z-promethee fuzzy-waspas fuzzy-marcos fuzzy-topsis fuzzy-mabac fuzzy-aras


ZF/MMSE Equalization

Zero-Forcing and Minimum Mean-Square Error Equalization

channel equalization
interference cancellation

Zero-Forcing (ZF) and Minimum Mean-Square Error (MMSE) equalization are fundamental linear receiver algorithms for combating intersymbol interference in dispersive channels. Developed in the context of data transmission theory, these methods form the basis of modern channel equalization in wireless and wired systems. While ZF aggressively cancels interference, MMSE balances interference suppression with noise enhancement, making it the optimal linear solution under Gaussian noise.

Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill.

Haykin, S. (2002). Adaptive Filter Theory (4th ed.). Prentice Hall.

ofdm mimo turbo-code shannon-capacity ldpc-codes


Ziegler-Nichols Tuning

Ziegler-Nichols Tuning is a practical, model-free method for tuning PID controller gains empirically. Published in 1942, this pioneering method requires only measurement of the system's step response (or closed-loop oscillations), making it applicable to any system without prior identification. Ziegler-Nichols remains widely used in industry because it is simple, fast, and often produces reasonable initial tunings.

Ziegler, J. G., & Nichols, N. B. (1942). Optimum settings for automatic controllers. Transactions of the American Society of Mechanical Engineers, 64(8), 759-768.

Astrom, K. J., & Hagglund, T. (2006). Advanced PID Control. ISA-The Instrumentation, Systems, and Automation Society.


Zivot-Andrews Structural Break Test

Zivot-Andrews Unit Root Test with Endogenous Structural Break

endogenous structural break unit root test

The Zivot-Andrews (ZA) test is a unit root test that endogenously identifies the most likely location of a single structural break in a time series. Unlike the standard ADF test, it does not require the researcher to pre-specify when the break occurred, making it robust to data-driven regime shifts such as policy changes, financial crises, or major economic events.

Unit root test with endogenous structural break

Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270.

Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361–1401.

augmented-dickey-fuller-unit-root-test phillips-perron-unit-root-test granger-causality-test engle-granger-cointegration-test arima-model vector-autoregression


Zivot-Andrews Test

Zivot-Andrews Unit-Root Test with One Structural Break

ZA Test
Zivot-Andrews Break Test
Endogenous Break Unit-Root Test
Zivot-Andrews Birim Kök Testi

The Zivot-Andrews (ZA) test, introduced by Eric Zivot and Donald Andrews in 1992, is a sequential unit-root test that allows for a single structural break at an unknown date. It extends the augmented Dickey-Fuller framework by endogenously selecting the break point that provides the strongest evidence against the unit-root null hypothesis, making it particularly useful for macroeconomic and financial time series that may have been disrupted by events such as policy changes, financial crises, or supply shocks.

Sequential unit-root test with endogenous break-point selection

Trend-stationary process with a single structural break


zk-SNARK

A zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) is a cryptographic proof system that allows a prover to convince a verifier that a statement is true without revealing any information beyond the statement's validity. The acronym describes its key properties: it requires no interaction, proofs are short (succinct), and verification is efficient. zk-SNARKs were popularized by their application in the Zcash cryptocurrency but have since found use in blockchain scaling solutions, privacy-preserving computations, and verifiable computing.

Ben-Sasson, E., Chiesa, A., Garman, C., Green, M., Miers, I., Tromer, E., & Virza, M. (2014). Zerocash: Decentralized Anonymous Payments from Bitcoin. In IEEE Symposium on Security and Privacy (SP), pp. 459-474.

Bünz, B., Bootle, J., Boneh, D., Poelstra, A., Wuille, P., & Maxwell, G. (2018). Bulletproofs: Short proofs for confidential transactions and more. In IEEE S&P 2018, pp. 315-334.


zk-STARK

zk-STARK
transparent argument of knowledge
STARK

A zk-STARK (Zero-Knowledge Scalable Transparent Argument of Knowledge) is a cryptographic proof system allowing a prover to convince a verifier of a computation's correctness without trusted setup or revealing computational details. Introduced by Ben-Sasson and colleagues in 2018, zk-STARKs address a key limitation of zk-SNARKs: they require no preprocessing phase vulnerable to corruption. Instead, STARKs rely only on cryptographic hash functions, making them simpler, more transparent, and believed to be post-quantum secure.

transparent zero-knowledge argument of knowledge

Ben-Sasson, E., Bentov, I., Horesh, Y., & Riabzev, M. (2019). Scalable, transparent, and post-quantum secure computational integrity. In IACR Cryptology ePrint Archive, Report 2018/046.

Ben-Sasson, E., Riabzev, M., Rozenkraut, M., Shacham, H., & Stemen, M. (2021). Aurora: Transparent Succinct Non-Interactive Zero-Knowledge Proofs. In IACR Cryptology ePrint Archive, Report 2018/828.


Zoonotic Disease Surveillance

Systematic Surveillance and Monitoring of Zoonotic Disease in Animal Populations

disease monitoring
epidemiological surveillance
public health surveillance

Veterinary epidemiology and public health

Zoonotic disease surveillance is a systematic population-level monitoring approach that detects, tracks, and analyzes cases of infectious diseases transmissible between animals and humans. Formalized through veterinary epidemiology and integrated with public health systems since the early 1900s, modern surveillance programs employ case detection networks, laboratory confirmation, and data sharing to enable early warning of emerging threats and coordinated disease prevention across animal and human sectors.

Kahn, C. M. (Ed.). (2002). The Merck Veterinary Manual (9th ed.). Whitehouse Station, NJ: Merck.

Zinsstag, J., Schelling, E., Waltner-Toews, D., Tanner, M. (2015). From 'One Medicine' to 'One Health' and systemic approaches to health and well-being. Preventive Veterinary Medicine, 120(1), 12-19.

Centers for Disease Control and Prevention (CDC). (2023). Zoonotic Diseases. Retrieved from CDC website: https://www.cdc.gov/zoonotic/index.html


Reference Management Software

Comparison and Selection of Zotero, Mendeley, and EndNote

reference manager
citation software
Zotero
Mendeley
EndNote

1989 (EndNote original); 2006 (Zotero); 2008 (Mendeley acquired by Elsevier)

Zotero (George Mason University, 2006); Mendeley (Elsevier, 2008 acquisition); EndNote (Clarivate, 1988 original; acquired 2016)

Zotero, Mendeley, and EndNote are the three most widely used reference management applications. Each helps researchers organize bibliographic references, annotate articles, and generate formatted citations and bibliographies. Zotero (launched 2006 by George Mason University) is free and open-source; Mendeley (acquired by Elsevier in 2008) offers a freemium model; EndNote (originally developed in 1989, now owned by Clarivate) is commercial. All three integrate with word processors and support multiple citation styles. Choosing between them depends on budget, collaboration needs, storage requirements, and preferred features.

Zotero project team (2024). Zotero: Free reference management software. https://www.zotero.org

Elsevier (2024). Mendeley reference management software. https://www.elsevier.com/products/mendeley

Clarivate (2024). EndNote reference management and collaboration software. https://endnote.com

citation-management-tools citation-analysis doi-system systematic-search-strategy


Zung Self-Rating Anxiety Scale

The Zung Self-Rating Anxiety Scale (ZRAS), also known as the Self-Rating Anxiety Scale (SAS), is a 20-item self-report measure of anxiety symptoms. Developed by William W. K. Zung in 1971, the ZRAS assesses psychological and somatic manifestations of anxiety in the past week. It is widely used for anxiety screening in primary care, general medical settings, and mental health research.

Zung, W. W. (1971). A rating instrument for anxiety disorders. Psychosomatics, 12(6), 371-379.

Dunstan, D. A., Scott, N., & Todd, A. K. (2005). Screening for anxiety and depression: Reassessing the utility of the Zung scales. BMC Psychiatry, 5, 8.