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Gain

Gain is an English noun and verb denoting the acquisition or achievement of profit, advantage, or benefit, as well as an increase in amount, magnitude, degree, or intensity.^[1] Etymologically, the term derives from Middle English gaynen (verb) and gain (noun), borrowed from Old French gaignier ("to cultivate, earn, or secure") and influenced by Old Norse gagn ("use, advantage"), ultimately tracing to Proto-Germanic roots associated with productive labor such as tillage or hunting yields.^[2]^[1] In everyday usage, gain encompasses financial profit from trade or investment, territorial or competitive advances, or physiological increments like weight or speed.^[1] Specialized applications abound in technical domains: in electronics and physics, gain quantifies signal amplification as the logarithmic ratio of output to input power or voltage, critical for devices like amplifiers and antennas.^[1] In biology and virology, gain-of-function research modifies organisms to enhance traits such as transmissibility or virulence, enabling insights into disease mechanisms, vaccine development, and pathogen evolution, though it has sparked debate over biosecurity risks versus scientific benefits.^[3]^[4] These meanings underscore gain's core connotation of positive differential outcome, grounded in causal processes of input transformation yielding superior outputs, while highlighting contexts where unintended escalations—such as in nuclear innovation initiatives like the U.S. Department of Energy's GAIN program—demand rigorous empirical validation.^[5]

Science and Technology

Amplifier and Signal Gain

In electronics and signal processing, gain refers to the ratio of the output signal amplitude to the input signal amplitude in an amplifier or system, quantifying the degree of amplification. For voltage gain, it is mathematically expressed as A_v = \frac{V_{out}}{V_{in}}, where V_{out} is the output voltage and V_{in} is the input voltage; similar definitions apply to current gain (A_i = \frac{I_{out}}{I_{in}}) and power gain (A_p = \frac{P_{out}}{P_{in}}). This measure assumes linear operation within the amplifier's specifications, as nonlinear distortion can alter effective gain. Amplifiers achieve gain through active devices such as bipolar junction transistors (BJTs), field-effect transistors (FETs), or operational amplifiers (op-amps), which exploit principles of carrier multiplication and energy transfer from a power supply. In a common-emitter BJT configuration, for instance, current gain (\beta or h_{fe}) typically ranges from 20 to 1000, enabling voltage amplification when combined with load resistors, as derived from the transistor's forward-active region characteristics where collector current I_C \approx \beta I_B. Op-amps, idealized as having infinite open-loop gain (often >10^5 in practice), provide controlled gain via negative feedback in configurations like the non-inverting amplifier, where closed-loop gain is A_v = 1 + \frac{R_f}{R_g}, with R_f and R_g as feedback and gain-setting resistors, respectively; this stability arises from feedback reducing sensitivity to device variations. Signal gain is often expressed in decibels (dB) for logarithmic scaling, facilitating analysis of cascaded systems: voltage gain in dB is $20 \log_{10} (A_v), while power gain uses $10 \log_{10} (A_p). A gain of 1 (0 dB) indicates no amplification, unity gain; values >1 (>0 dB) denote amplification, and <1 (<0 dB) attenuation. In practice, maximum gain is limited by factors like thermal noise, bandwidth (per the gain-bandwidth product, e.g., 1 MHz for common op-amps), and stability margins to avoid oscillations, as quantified by phase margin in Bode plots. For example, the LM741 op-amp exhibits a typical open-loop gain of 100 dB at DC, rolling off at 20 dB/decade beyond its unity-gain frequency. In communication systems, signal gain compensates for losses in transmission paths, such as in radio frequency (RF) amplifiers where power gain ensures sufficient signal-to-noise ratio (SNR) at the receiver; Friis transmission equation relates effective isotropic radiated power (EIRP) to gain, underscoring that directional antennas pair with amplifiers to boost effective gain without increasing input power. Real-world measurements, standardized by bodies like the IEEE, account for impedance matching to maximize power transfer, as mismatch reduces available gain per the reflection coefficient \Gamma = \frac{Z_L - Z_0}{Z_L + Z_0}. Excessive gain can introduce instability or intermodulation distortion in multi-stage systems, necessitating automatic gain control (AGC) circuits that dynamically adjust gain based on input levels, as implemented in audio and RF receivers since the 1930s.

Antenna and Directional Gain

Antenna gain quantifies the ability of an antenna to concentrate electromagnetic power in a particular direction relative to a hypothetical isotropic radiator that distributes power uniformly in all directions.^[6] It is defined as the ratio of the radiation intensity in the direction of maximum radiation to the radiation intensity that would be produced by an isotropic radiator with the same total radiated power, typically expressed in decibels relative to an isotropic source (dBi).^[7] For instance, an antenna with 3 dBi gain radiates twice the power in its peak direction compared to an isotropic antenna fed with the same input power.^[6] Antenna gain differs from directivity, which measures the theoretical concentration of radiated power without accounting for losses such as ohmic resistance or dielectric dissipation in the antenna structure.^[8] Directivity D is the ratio of the power density in a specified direction to the average power density over all directions at the same distance from the antenna, given by D = \frac{4\pi U(\theta, \phi)_{\max}}{P_{\rad}}, where U(\theta, \phi)_{\max} is the maximum radiation intensity and P_{\rad} is the total radiated power.^[9] Gain G incorporates antenna efficiency \eta (the ratio of radiated power to input power, typically 0 to 1), such that G = \eta \cdot D.^[9] Thus, for lossless antennas, gain equals directivity; real antennas exhibit gain less than directivity due to inefficiencies, often by several percent in high-quality designs.^[8] Directional gain specifically refers to the gain value in a chosen direction, emphasizing the antenna's non-uniform radiation pattern that favors certain azimuths or elevations to enhance signal strength along desired paths, such as in point-to-point links or radar systems.^[10] Higher directional gain correlates inversely with beamwidth: narrower beams achieve greater gain by focusing energy, as per the approximate relation G \approx \frac{41253}{\theta \cdot \phi} in degrees for the product of half-power beamwidths \theta and \phi.^[10] Measurements of gain involve comparing the antenna under test to a standard gain horn or using the three-antenna method in an anechoic chamber, ensuring far-field conditions where distance exceeds $2D^2 / \lambda (D is aperture size, \lambda is wavelength).^[11] Common units include dBi for absolute gain relative to isotropic and dBd relative to a half-wave dipole, which itself has 2.15 dBi gain, allowing conversion via \text{dBi} = \text{dBd} + 2.15.^[12] In practice, parabolic dish antennas can achieve 20-40 dBi for microwave frequencies by virtue of large apertures, while Yagi-Uda arrays yield 10-15 dBi for VHF/UHF applications.^[6] The Friis transmission equation, P_r = P_t G_t G_r \left( \frac{\lambda}{4\pi R} \right)^2 , underscores gain's role in linking transmit and receive powers P_t, P_r over distance R, highlighting its causal impact on link budgets in wireless systems.^[13]

Information Gain in Computing

Information gain is a metric employed in machine learning, particularly in decision tree induction algorithms, to assess the effectiveness of a candidate attribute for partitioning a dataset. It measures the reduction in uncertainty, quantified as entropy, achieved by splitting the data based on the attribute's values. This approach selects attributes that maximize the differential between the entropy of the original dataset and the weighted average entropy of the resulting subsets, thereby prioritizing splits that best separate classes.^[14] The concept originates from the ID3 (Iterative Dichotomiser 3) algorithm, developed by J. Ross Quinlan and published in 1986. In ID3, information gain guides the greedy, top-down construction of decision trees by iteratively choosing the attribute with the highest gain at each node until a stopping criterion, such as pure subsets or maximum depth, is met. Quinlan defined entropy H(S) for a dataset S with class probabilities p_i as H(S) = -\sum p_i \log_2 p_i, representing the expected information required to identify a class label. The information gain IG(A) for attribute A is then IG(A) = H(S) - \sum_{v \in \text{values}(A)} \frac{|S_v|}{|S|} H(S_v), where S_v denotes the subset of S with value v for A.^[14] This formulation draws from information theory, where entropy captures impurity or unpredictability in class distribution, and gain reflects mutual information between the attribute and the target class. In practice, ID3 applies information gain recursively, handling discrete attributes and assuming independence among features conditional on the path. Extensions like C4.5, also by Quinlan in 1993, addressed limitations by introducing gain ratio to mitigate bias toward attributes with numerous values, as raw information gain favors such attributes due to finer partitions yielding lower weighted entropy regardless of class separation quality. Gain ratio normalizes by split information \text{SplitInfo}(A) = -\sum_{v \in \text{values}(A)} \frac{|S_v|}{|S|} \log_2 \frac{|S_v|}{|S|}, yielding \text{GainRatio}(A) = \frac{IG(A)}{\text{SplitInfo}(A)}. Empirical studies confirm gain ratio reduces overfitting and improves generalization compared to unnormalized gain, particularly on datasets with high-cardinality features.^[14] Applications extend beyond ID3 to ensemble methods like random forests, where information gain variants inform initial splits, and to feature selection in broader supervised learning pipelines. However, its sensitivity to small datasets or noisy data can lead to unstable trees, prompting hybrid criteria like Gini impurity in algorithms such as CART, which approximate entropy but compute faster via \text{Gini}(S) = 1 - \sum p_i^2. Despite these alternatives, information gain remains foundational for its interpretability and direct ties to probabilistic impurity reduction.

Health and Physiology

Weight Gain

Weight gain occurs when body mass increases over time, primarily through accumulation of adipose tissue, but also via muscle hypertrophy, fluid retention, or bone density changes. Physiologically, it stems from a sustained positive energy balance where caloric intake exceeds expenditure, leading to storage of excess energy as triglycerides in adipocytes. This process is governed by the first law of thermodynamics applied to human metabolism, where unutilized energy cannot be destroyed but is conserved as fat.^[15] In experimental overfeeding studies, participants exhibit reduced spontaneous food intake and potential elevations in energy expenditure as compensatory mechanisms, though these are often insufficient to prevent net gain.^[16] Key drivers include dietary factors, such as consumption of energy-dense foods, which disrupt energy homeostasis. Hormonal regulation plays a critical role: insulin promotes fat storage by facilitating glucose uptake into cells, while leptin signals satiety via hypothalamic pathways, though resistance develops in chronic overnutrition states. Genetic predispositions influence susceptibility, with variants in genes like MC4R accounting for up to 30% of severe early-onset obesity cases by altering appetite and energy partitioning. Environmental contributors, including sedentary behavior and sleep disruption, exacerbate imbalance by lowering basal metabolic rate and increasing orexigenic signals.^[17]^[18]^[19] Measurement typically involves body mass index (BMI), calculated as weight in kilograms divided by height in meters squared, with gains exceeding 5-10% of baseline mass signaling clinically relevant changes. Dual-energy X-ray absorptiometry (DEXA) distinguishes fat from lean mass, revealing that much weight gain in adults is adiposity-driven rather than muscular.^[20] Health consequences vary by context: moderate gain benefits underweight individuals by improving immune function and reducing frailty risks, but excessive accumulation—defining obesity as BMI ≥30 kg/m²—elevates morbidity from type 2 diabetes, cardiovascular disease, and certain cancers via insulin resistance, inflammation, and mechanical stress on joints. Peer-reviewed meta-analyses confirm a J-shaped mortality curve, where both underweight (BMI <18.5) and obesity correlate with higher all-cause death rates relative to normal weight, though obesity's risks predominate in population data.^[21]^[22]^[23]

Muscle and Strength Gain

Muscle hypertrophy, or muscle gain, refers to an increase in the cross-sectional area of skeletal muscle fibers primarily through resistance exercise training (RET), while strength gain involves enhanced force production capability, initially driven by neural adaptations and later by hypertrophic changes.^[24] ^[25] Early strength improvements in novices, often within the first 4-8 weeks of training, stem from neuromuscular enhancements such as increased motor unit recruitment, firing rates, and intermuscular coordination, rather than substantial muscle size increases.^[26] ^[27] These neural adaptations can account for up to 50-80% of initial strength gains, with hypertrophy contributing more prominently after 8-12 weeks as mechanical tension from progressive overload stimulates protein synthesis via pathways like mTOR and IGF-1 signaling.^[28] ^[29] Key mechanisms of hypertrophy include mechanical tension from heavy loads, metabolic stress from higher repetitions, and limited muscle damage repaired via satellite cell fusion, though evidence suggests tension as the primary driver over damage or stress alone.^[30] RET protocols optimizing hypertrophy typically involve moderate loads (60-80% of one-repetition maximum, 6-12 repetitions per set) performed 2-3 times weekly per muscle group, with volume (sets × reps × load) progressively increased to elicit adaptation; meta-analyses confirm such training yields 0.5-1 kg lean mass gains over 8-12 weeks in untrained adults.^[31] ^[32] For strength, heavier loads (>80% one-repetition maximum, 1-6 reps) enhance neural drive and fiber-specific hypertrophy in type II fibers, producing superior force outputs compared to hypertrophy-focused regimens, though both overlap in benefits.^[33] Single-set training to near-failure can achieve comparable hypertrophy to multi-set protocols in some populations, but higher volumes generally yield greater gains in trained individuals.^[34] Nutrition plays a supportive role, with meta-analyses showing that protein intakes of 1.6-2.2 g/kg bodyweight daily enhance lean mass and strength gains during RET by 0.2-0.5 kg more than lower intakes, primarily via elevated muscle protein synthesis rates post-exercise.^[35] ^[36] An energy surplus of 250-500 kcal/day facilitates hypertrophy but is not strictly required if protein is adequate, as deficits can still yield gains with preserved lean mass; timing protein around workouts (20-40 g doses) offers marginal benefits over total daily intake.^[37] ^[38] Recovery factors like 48-72 hours between sessions for the same muscle group and 7-9 hours of sleep nightly support hormonal regulation (e.g., testosterone, growth hormone) essential for sustained adaptation.^[39] Individual variability influences outcomes: genetics account for 40-70% of muscle mass potential, with men typically gaining faster due to higher testosterone (e.g., 5-10 kg lean mass in first year vs. 2-5 kg for women), while aging reduces responsiveness by 1% annually post-30 via attenuated satellite cell activity.^[40] ^[41] Longitudinal studies indicate plateaus after 1-2 years without periodization, emphasizing progressive overload to overcome; anabolic agents like β2-agonists induce hypertrophy via AKT/mTOR but carry health risks and are not recommended for natural training.^[40] ^[42]

Economics and Finance

Profit and Income Gain

Profit, in economic terms, constitutes the financial gain realized by a business when total revenue exceeds total costs, encompassing both explicit outlays like wages and materials and implicit opportunity costs of resources employed.^[43] ^[44] Accounting profit, calculated as revenue minus explicit costs, differs from economic profit, which subtracts both explicit and implicit costs to reflect true resource allocation efficiency.^[45] Firms achieve profit gains through mechanisms such as revenue expansion via higher sales volumes or prices, and cost reductions from operational efficiencies or supply chain optimizations.^[46] Empirical evidence indicates variability across sectors; for instance, U.S. corporate profits in wholesale trade reached approximately 290.5 billion dollars in 2023, driven by trade volume increases, while S&P 500 companies reported net profit margins exceeding 12% in the first two quarters of 2025, reflecting resilient earnings amid economic recovery.^[47] ^[48] Income gain refers to the net increase in an individual's or household's monetary receipts from sources like wages, salaries, or supplemental earnings, distinct from one-off capital gains tied to asset sales.^[49] ^[50] Such gains arise causally from labor market dynamics, including skill acquisition leading to higher wages or employment shifts to higher-paying roles, as well as macroeconomic factors like productivity growth enabling wage adjustments.^[51] In the U.S., real average hourly earnings rose 1.1% from August 2024 to August 2025, adjusted for inflation, signaling modest gains amid moderating nominal wage pressures.^[52] The national average wage index climbed to 69,846.57 in 2024, a 4.84% increase over 2023, underscoring cumulative income elevation from sustained employment and output per worker.^[53] Profit and income gains interconnect in market economies, where business profits fund expansions that generate jobs and wage opportunities, while individual income rises bolster consumer demand supporting firm revenues.^[54] However, external shocks like supply disruptions or regulatory changes can erode margins; for example, non-financial corporate profits declined in late 2023 despite elevated margins, highlighting the role of volume in sustaining gains.^[55] Tax policies influence realization, with income gains from operations taxed as ordinary income, whereas certain profit distributions may qualify for preferential rates, affecting net retention.^[56] Long-term sustainability demands alignment with productivity, as unsubstantiated gains risk reversal through competition or cost inflation.^[57]

Capital Gains and Asset Appreciation

Capital gains represent the profit realized upon the sale of a capital asset, calculated as the difference between the asset's selling price and its adjusted cost basis, which accounts for the original purchase price plus adjustments such as improvements or depreciation.^[58] ^[59] These gains typically arise from assets held for investment purposes, including stocks, bonds, real estate, and mutual funds, and are distinguished from ordinary income by their source in asset sales rather than wages or services.^[60] Asset appreciation forms the underlying mechanism for capital gains, referring to the increase in an asset's market value over time due to factors such as economic growth, supply-demand dynamics, inflation, or improved asset fundamentals like corporate earnings in equities.^[61] ^[62] Unlike depreciation, which erodes value through wear or obsolescence, appreciation can occur passively without owner intervention, as seen in land or collectibles where scarcity drives rising prices.^[63] Realized capital gains only materialize upon sale, while unrealized appreciation—paper gains—remains untaxed until disposition, allowing deferred taxation that incentivizes long-term holding.^[64] In equity markets, historical data illustrates appreciation's role: the S&P 500 index has delivered an average annual nominal return of approximately 10.4% from 1957 through April 2025, equating to about 6.5% after inflation adjustment, primarily through price appreciation and dividends.^[65] This compounding effect underscores capital gains' contribution to wealth accumulation, with studies showing that reinvested gains and savings from appreciated assets explain much of the rise in top-wealth portfolios, where gross saving rates including capital gains rise sharply with wealth levels.^[66] For real estate, median home prices in the U.S. appreciated at an average annual rate of around 4-5% from 1963 to 2023, adjusted for inflation, amplifying gains for holders during periods of housing booms.^[67] Taxation of capital gains varies by jurisdiction and holding period, with the U.S. distinguishing short-term gains (assets held one year or less), taxed at ordinary income rates up to 37%, from long-term gains, taxed at preferential rates of 0%, 15%, or 20% for 2025 based on taxable income thresholds—0% for singles up to $48,350, 15% up to $533,400, and 20% thereafter.^[68] ^[69] These lower long-term rates, rooted in policy favoring investment retention over frequent trading, reduce the effective tax burden on appreciation, thereby supporting capital formation; however, an additional 3.8% net investment income tax applies to high earners, pushing top effective rates to 23.8%.^[70] Empirical analyses indicate that such taxation structures promote wealth growth by minimizing distortions in saving and investment decisions, though debates persist on whether unrealized gains should face annual levies, as proposed in some reforms but critiqued for liquidity challenges absent actual sales.^[64] Economically, capital gains from asset appreciation drive intergenerational wealth transfer and portfolio diversification, with data showing they constitute a primary channel for inequality dynamics—rising during bull markets to concentrate gains among asset owners, while recessions can erase them, as in 2008 when U.S. household net worth fell 20% due to asset value drops.^[71] Despite media portrayals emphasizing inequity, causal evidence links realized gains to productive reinvestment, fostering innovation and growth, as opposed to consumption-driven income; for instance, post-1980s U.S. data attributes 8% of national income growth to capital gains realizations, excluded from standard GDP but vital for balance sheet expansion.^[72] Investors mitigate risks through strategies like tax-loss harvesting, offsetting gains with losses to lower net taxable amounts, enhancing after-tax returns essential for sustained accumulation.^[60]

Gain Framing in Decision-Making

Gain framing refers to the presentation of decision options in terms of potential positive outcomes or benefits, as opposed to losses, influencing preferences under prospect theory developed by Daniel Kahneman and Amos Tversky in 1979.^[73] In this framework, individuals evaluate prospects relative to a reference point, exhibiting risk aversion when choices are framed as gains because a sure gain is preferred over a probabilistic one of equal expected value.^[74] This contrasts with loss framing, where risk-seeking behavior emerges to avert certain losses, highlighting how equivalent descriptions yield divergent choices due to cognitive biases rather than rational utility maximization.^[75] A seminal demonstration appears in Tversky and Kahneman's 1981 study on the "Asian disease problem," where participants faced hypothetical policy choices for combating an outbreak expected to kill 600 people.^[74] In the gain frame, options were: "200 people will be saved" (certain) versus a one-third chance to save 600 with a two-thirds chance of saving none (risky); 72% selected the certain option.^[74] Reframed as losses—"400 people will die" (certain) versus a one-third chance none die and two-thirds chance 600 die—only 22% chose the certain outcome, favoring the gamble.^[74] This reversal persists across replications, with meta-analyses confirming moderate effect sizes (e.g., Cohen's d ≈ 0.3-0.5) for risky-choice framing in gain versus loss conditions.^[76] Applications extend to behavioral economics and policy, where gain framing promotes risk-averse decisions in domains like health promotion and environmental compliance. For instance, messages emphasizing gains (e.g., "exercise to gain health benefits") encourage preventive behaviors more than loss-framed warnings, with effect sizes up to d = 0.47 in attitude and intention shifts.^[76] In economic contexts, gain-framed incentives, such as tax rebates described as savings, increase compliance over penalties framed as losses, though outcomes vary by task repetitiveness and payoff structure.^[77] During crises like COVID-19, gain frames (e.g., "vaccination saves lives") boosted risk-averse preferences for mitigation over loss frames highlighting deaths averted.^[78] Criticisms note that prospect theory's framing mechanism inadequately explains frame generation or processing, relying on ad hoc reference points without detailing cognitive pathways, and struggles with group-level decisions or complex real-world multiplicities.^[79] ^[80] Effects diminish under conditions altering equate-to-differentiate strategies or when frames align with intuitive gist representations, suggesting bounded rather than universal applicability.^[81] Despite this, empirical robustness across lab and field studies affirms gain framing's role in systematic preference reversals, challenging expected utility models.^[76]

Gain-Loss Dynamics in Psychology

Gain-loss dynamics in psychology describe the asymmetric psychological impact of gains and losses relative to a reference point, where losses typically evoke stronger emotional and behavioral responses than equivalent gains. This phenomenon, formalized in prospect theory by Daniel Kahneman and Amos Tversky in 1979, posits that individuals evaluate outcomes not in absolute terms but relative to a subjective reference level, leading to reference dependence.^[82] The theory's value function is S-shaped: concave for gains, reflecting risk aversion in positive domains, and convex for losses, indicating risk-seeking behavior to avoid certain losses; moreover, the function is steeper for losses than gains, embodying loss aversion with an estimated coefficient λ ≈ 2.25, meaning losses loom approximately twice as large as gains.^[73]^[83] Empirical support for loss aversion derives from controlled experiments, such as choice tasks where participants reject gambles with equal expected value but potential loss (e.g., 50% chance to gain $150 vs. 50% chance to lose $100), replicating across cultures and contexts with a global study in 2020 confirming Kahneman and Tversky's foundational results in 19 countries.^[84] Meta-analyses of over 200 studies estimate average loss aversion parameters between 1.8 and 2.5, though effects diminish in repeated experience-based decisions without explicit probabilities and vary by domain, such as weaker in low-stakes or aggregate outcomes.^[85] These dynamics underpin related biases, including the endowment effect—where ownership increases perceived value due to loss framing of selling—and status quo bias, as maintaining the current state avoids the pain of loss more than pursuing equivalent gain.^[86] In psychological applications, gain-loss asymmetry influences risk perception and decision-making under uncertainty, with loss-framed messages (e.g., emphasizing preventable harm) more persuasive for health behaviors than gain-framed ones, though efficacy depends on task framing—risk-averse for gains, risk-seeking for losses.^[87] Neuroimaging evidence links this to heightened amygdala activation for losses, supporting causal realism in emotional processing over neutral valuation.^[88] Critically, while robust in hypothetical and incentivized lab settings, real-world generalizability faces scrutiny, as initial evidence for prospect theory relied on high-stakes vignettes with limited replication until broader datasets; nonetheless, the core asymmetry persists across behavioral economics and clinical psychology, informing interventions like framing therapies for anxiety disorders rooted in loss hypersensitivity.^[89]^[90]

Named Entities and Other Uses

People with the Surname Gain

Bob Gain (June 21, 1929 – November 14, 2016) was an American professional football defensive tackle who played 13 seasons with the Cleveland Browns of the National Football League (NFL), appearing in 158 games from 1952 and 1954 to 1964. A two-way starter and placekicker at the University of Kentucky from 1947 to 1950, Gain earned All-America honors and contributed 38 extra points as kicker. After a brief NFL stint in 1952, he served as a first lieutenant in the U.S. Air Force during the Korean War in 1953 before returning to the Browns, where he helped secure three NFL championships in 1954, 1955, and 1964, and earned five Pro Bowl selections (1957, 1958, 1959, 1960, 1962).^[91]^[92]^[93] Charles Gain (November 1, 1923 – August 21, 2018) was an American police administrator who led the Oakland Police Department as chief from 1964 to 1973 and the San Francisco Police Department from 1975 to 1980. Born in Hanford, California, Gain began his career in Oakland in 1946 and pursued reforms emphasizing community-oriented policing, reduced use of force, and civilian oversight amid 1960s civil unrest, including responses to events like the Zebra murders in San Francisco. His tenure drew praise from civil rights advocates for progressive changes but criticism from officers and politicians for perceived leniency, which some linked to rising crime rates and declining morale; San Francisco's mayor replaced him in 1980 with a career officer. Gain died of respiratory failure at age 94.^[94]^[95] Peter Gain (born November 11, 1976) is a retired Irish professional footballer who played as a left midfielder, accumulating over 400 appearances in English Football League divisions. Starting his career at Reading, Gain featured prominently for Lincoln City from 1998 to 2005, making 231 league appearances and contributing to promotion efforts, before moving to clubs including Dagenham & Redbridge, where he played until 2009. Capped at youth international level for Ireland, he later transitioned to coaching roles in non-league football.^[96]^[97]

Commercial Brands and Products

Gain is a brand of laundry detergents, fabric care products, and dishwashing liquids produced by Procter & Gamble (P&G), launched in the United States in 1969 as an enzyme-based powder detergent targeted at stain removal and positioned as a more affordable alternative to P&G's flagship Tide brand. Initially struggling to gain market share among cost-conscious consumers, the brand underwent a strategic repositioning in 1981 to emphasize long-lasting fragrances, coinciding with the introduction of its first liquid detergent variant amid rising demand for convenient formats. By 2007, Gain had achieved billion-dollar brand status within P&G's portfolio, driven by its focus on scent innovation and expanded product lines.^[98]^[99]^[100] The brand's product lineup includes liquid and powder laundry detergents, laundry pacs (dissolvable pods), in-wash scent boosters like Gain Fireworks, fabric softeners, dryer sheets, and dish detergents, with formulations compatible with high-efficiency (HE) washing machines and available in scents such as Original, Spring Daydream, and limited-edition varieties like Apple + Mango Tango. Gain products are marketed for their ability to lift dirt while imparting scents that persist for weeks, with recent innovations including dual-bead scent boosters combining floral and fruity notes for up to 12 weeks of fragrance release. These items are distributed through major retailers like Walmart, Target, and Amazon, and are formulated for both household and commercial use in some variants.^[101]^[102]^[103] Consumer testing and reviews position Gain as a mid-tier performer in stain removal compared to premium brands like Tide or Persil, but it excels in scent retention, appealing to users prioritizing fragrance over maximum cleaning power. P&G continues to promote Gain through advertising campaigns highlighting scent longevity and collaborations, such as the 2025 "Get Scent to Oz" tie-in with Universal Pictures' Wicked film, featuring themed scent boosters. No other major commercial brands or product lines directly named "Gain" dominate distinct categories, though the term appears in generic weight-gainer supplements unrelated to P&G's ownership.^[104]^[105]

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### Summary of "Gain" Definitions (Merriam-Webster)
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An Evidence-Based Narrative Review of Mechanisms of Resistance ...
We provide up-to-date, evidence-based perspectives of the mechanisms regulating RET-induced skeletal muscle hypertrophy.
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Hypertrophy Training vs. Strength Training: Pros and Cons - Healthline
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Neuromuscular adaptations to resistance training in elite versus ...
Jun 9, 2025 · Early-phase strength gains in novice athletes are primarily driven by neural adaptations, as the nervous system becomes more efficient at ...
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The adaptations to strength training : morphological and ... - PubMed
Indirect evidence for neurological adaptations, which encompasses learning and coordination, comes from the specificity of the training adaptation, transfer of ...
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Molecular Mechanisms of Skeletal Muscle Hypertrophy - PMC
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Mechanisms of mechanical overload-induced skeletal muscle ...
This review first provides a historical account of how mechanistic research into skeletal muscle hypertrophy has progressed.
[30]
Anabolic signals and muscle hypertrophy – Significance for strength ...
In this narrative review, we examine the primary mechanisms driving muscle growth, including mechanical tension, metabolic stress, and muscle damage, and their ...
[31]
Loading Recommendations for Muscle Strength, Hypertrophy ... - NIH
Specifically, the theory postulates that heavy load training optimizes increases maximal strength, moderate load training optimizes increases muscle hypertrophy ...
[32]
Resistance Training Load Effects on Muscle Hypertrophy and ... - NIH
Untrained participants exhibit greater muscle hypertrophy, whereas undertaking more RT sessions provides superior gains in those with previous training ...
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Greater Neural Adaptations following High- vs. Low-Load ... - Frontiers
Our data suggest that high-load training results in greater neural adaptations that may explain the disparate increases in muscle strength.Abstract · Introduction · Methods · Discussion
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Build Strength and Muscle With Single-Set Training, Says Study
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Systematic review and meta‐analysis of protein intake to support ...
In conclusion, increasing daily protein ingestion results in small additional gains in LBM and lower body muscle strength gains in healthy adults enrolled in ...
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A systematic review, meta-analysis and meta-regression of the effect ...
Dietary protein supplementation significantly enhanced changes in muscle strength and size during prolonged RET in healthy adults.
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Is an Energy Surplus Required to Maximize Skeletal Muscle ...
While a recent meta-analysis suggested dietary protein supplementation enhances resistance training induced gains in muscle mass and strength, at least when ...Introduction · Energy Balance · Energy Surplus… How Much · Energy Surplus...
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The effect of protein timing on muscle strength and hypertrophy
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Regulation of muscle hypertrophy: Involvement of the Akt ...
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Mechanisms of muscle atrophy and hypertrophy - Nature
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Mechanisms regulating skeletal muscle growth and atrophy
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Synergistic Effect of Increased Total Protein Intake and Strength ...
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Economic Profit - Definition, Formula, and Examples
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Profit refers to a company's surplus revenue after accounting for its costs and expenses during a certain period, such as a quarter or fiscal year.What Is Profit? · How Profit Is Calculated · Gross Profit · Operating Profit
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Two factors affecting profit margins are quantitative, like net profits and sales earnings, and qualitative, such as market share and consumer preferences.
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S&P 500 Reporting Net Profit Margin Above 12% for the 3rd Straight ...
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Gains: Meaning and Examples of a Transaction Outcome
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What is the difference between revenue, income, and gain?
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[PDF] Monetary Policy Report June 2025 - Federal Reserve Board
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Understanding Profitability | Ag Decision Maker
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Appreciation vs. Depreciation Explained: Key Financial Examples
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Appreciation - Definition, Meaning, Usage Examples
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Understanding capital gains: The first step to better after-tax outcomes
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[PDF] Saving Behavior Across the Wealth Distribution
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Oct 9, 2025 · Capital gains tax rate 2025 ; 0%. $0 to $48,350. $0 to $96,700 ; 15%. $48,351 to $533,400. $96,701 to $600,050 ; 20%. $533,401 or more. $600,051 or ...Capital Gains Tax Calculator · Federal Income Tax Brackets · Tax-Loss Harvesting
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2025 Tax Brackets and Federal Income Tax Rates | Tax Foundation
Oct 22, 2024 · Table 6. 2025 Capital Gains Tax Brackets ; 15%, $48,350, $96,700, $64,750 ; 20%, $533,400, $600,050, $566,700 ...
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Accounting for capital gains in income significantly increases U.S. ...
Jul 15, 2025 · Adding capital gains to other forms of income can thus both increase and decrease inequality. During recessions, when asset values plunge, ...
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[PDF] CAPITAL GAINS AND THE DISTRIBUTION OF INCOME IN THE ...
Since 1980, capital gains have driven wealth accumulation, averaging 8% of national income, and are not included in national income accounts. They are measured ...
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[PDF] Prospect Theory: An Analysis of Decision under Risk - MIT
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[PDF] The Framing of Decisions and the Psychology of Choice
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Frames, Biases, and Rational Decision-Making in the Human Brain
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A systematic review of risky-choice framing effects - PubMed Central
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Loss and gain framing to encourage repeated real-effort provision
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The Effect of Gain-versus-Loss Framing of Economic and Health ...
Nov 8, 2021 · Replicating prospect theory in an ecologically valid crisis context, we found that gain frames promoted risk-aversive preferences, whereas loss ...
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Prospect Theory - Overview, Phases, and Features
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[PDF] A critique of prospect theory and framing with particular reference to ...
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Prospect Theory: An Analysis of Decision under Risk - jstor
The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains.
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[PDF] Loss Aversion in Riskless Choice: A Reference-Dependent Model
Much experimental evidence indicates that choice depends on the status quo or reference level: changes of reference point often lead to reversals of ...
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[PDF] The Endowment Effect, Loss Aversion, and Status Quo Bias
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Loss aversion, the endowment effect, and gain-loss framing shape ...
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Kahneman and Tversky's “debatable” loss aversion assumption
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Bob Gain Stats, Height, Weight, Position, Draft, College
Bob Gain. Robert Gain. Position: DT-DE-MG-T. 6-3, 256lb (190cm, 116kg). Born: June 21, 1929 in Akron, OH. Died: November 14, 2016 in Willoughby, OH.
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Bob Gain, Star Defensive Lineman on Browns Title Teams, Dies at 87
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Charles Gain, controversial SF police chief during turbulent '70s, dies
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Charles Gain, former Oakland and SF police chief, dead at 94
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Peter Gain Biography - ESPN Global
View the biography of Dagenham & Redbridge Midfielder Peter Gain on ESPN. Includes career history and teams played for.Missing: notable person
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Sep 4, 2007 · Gain was nearly a loss for Procter & Gamble. The low-priced laundry detergent, launched in 1969, had grown a small following among cost-conscious consumers.
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Procter & Gamble Announces Gain As Its 23rd Billion-Dollar Brand
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Gain Logo and symbol, meaning, history, PNG, brand - 1000 Logos
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Gain Laundry and Dish Detergent, Fabric Softener | Gain
Gain offers a wide variety of fresh smelling laundry detergents, fabric softeners, dryer sheets, dish detergents and more. Take a look and find your scent.
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Gain's® New Dual Bead In-Wash Scent Boosters Deliver Powerful ...
May 1, 2025 · Gain Tango Scent Boosters, which come in Strawberry + Shea and Piña + Plumeria scent varieties, add delight by providing bursts of fragrance up to 12 weeks ...
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P&G Professional Gain Powder Laundry Detergent for Regular and ...
Gain laundry detergent works in both HE and regular machines, and the detergent lifts away dirt and locks in amazing scent to keep your laundry smelling great ...
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Gain Original Liquid Laundry Detergent Review - Consumer Reports
We've tested and reviewed products since 1936. Read CR's review of the Gain Original Liquid laundry detergent to find out if it's worth it.
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Gain®, Febreze® and Dawn® Announce “Get Scent to Oz ...
Oct 6, 2025 · Gain®, Febreze® and Dawn® Announce “Get Scent to Oz” Collaboration in Partnership With Universal Pictures' Wicked: For Good.Missing: commercial | Show results with:commercial