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Range

Range: Why Generalists Triumph in a Specialized World is a 2019 non-fiction book by science journalist David Epstein, which contends that individuals with diverse experiences and broad knowledge bases—termed "generalists"—often outperform early specialists in unpredictable and multifaceted fields such as , forecasting, and scientific discovery. Drawing on case studies from athletics, music, and research, Epstein illustrates how figures like tennis player , who sampled multiple sports before focusing, achieved superior adaptability compared to those like golfer , who specialized young in more predictable "kind" environments. Epstein structures his argument around the distinction between "kind" learning environments, where narrow expertise yields rapid gains, and "wicked" ones, characterized by novelty and incomplete feedback, where interdisciplinary "range" fosters creativity and problem-solving through analogies across domains. He advocates for extended "sampling periods" in and careers to build transferable skills, critiquing the pressure for premature that can limit in dynamic contexts, supported by evidence from polymathic inventors and military forecasters who integrated outsider perspectives. The book builds on Epstein's prior work, The Sports Gene, by shifting from genetic factors in performance to experiential breadth, urging readers to embrace inefficiency in exploration for long-term efficacy in an era of .

Mathematics and Statistics

Range of a function

The f: X \to Y, where X is the and Y is the , is the of X under f, defined as the set \{f(x) \mid x \in X\} \subseteq Y. This set comprises precisely those elements of the codomain that are attained as outputs for some input in the domain. The Y is part of the function's specification and may contain elements not reached by f; the range is always a of Y, potentially proper. If the range equals the , the function is surjective (onto). In contrast, some educational contexts, particularly in introductory , loosely use "range" to denote the , but this conflates specification with attainment and is imprecise in set-theoretic . Determining the range requires analyzing the function's behavior over its . For continuous functions on closed intervals, such as polynomials, the range can be found via critical points and endpoint evaluations using ; for example, the f(x) = x^2 on \mathbb{R} has range [0, \infty), as the minimum value is 0 at x=0. Discrete functions, like f: \mathbb{N} \to \mathbb{N} given by f(n) = n^2, yield ranges \{1, 4, 9, \dots\}, excluding non-squares. Piecewise or absolute value functions may require case-by-case evaluation, ensuring all branches are considered. In applications, the range informs feasibility: for instance, in optimization, it identifies achievable outcomes, while in , it reveals output constraints. Notationally, the range is often written as \operatorname{range}(f) or \operatorname{im}(f), emphasizing its role as the actual rather than the intended .

Statistical range as dispersion

The statistical range, a fundamental measure of in , quantifies the spread of by subtracting the minimum value from the maximum value in a , expressed as R = X_{\max} - X_{\min}, where X_i represents the observations. This yields the over which the vary, providing an immediate sense of variability without requiring complex computations. For instance, in a of exam scores {65, 72, 80, 92, 98}, the range is $98 - 65 = 33, indicating the scores extend across 33 points. As a dispersion metric, the highlights the extent of data scattering, with larger values signaling greater heterogeneity and smaller values implying tighter clustering around central tendencies. It proves useful in preliminary data exploration or when datasets are small and normally distributed, as it captures the full extent of extremes. However, its reliance solely on two endpoints renders it vulnerable to outliers; a single anomalous value can inflate [R](/page/R) disproportionately, misrepresenting the typical spread. Consequently, it underutilizes intermediate data points and lacks robustness for skewed or non-normal distributions, where alternatives like the or standard deviation offer more stable insights into central variability. To mitigate some limitations, the coefficient of range normalizes relative to the data's scale, computed as \frac{X_{\max} - X_{\min}}{X_{\max} + X_{\min}}, yielding a unitless proportion between 0 and 1 that facilitates comparisons across datasets of differing magnitudes. A value near 0 denotes minimal , while approaching 1 indicates high variability. Despite its simplicity—requiring only sorting and subtraction—the range's sensitivity to sampling variability and extremes confines its role to supplementary analysis rather than primary inference in rigorous statistical modeling.

Mid-range statistic

The mid-range is a measure of in statistics, defined as the of the minimum and maximum values in a . It is computed using the formula \frac{x_{\min} + x_{\max}}{2}, where x_{\min} is the smallest observation and x_{\max} is the largest. This approach requires sorting the data only to identify the extremes, making it computationally simple and fast, particularly for small samples. In contrast to the , which weights all data points equally, or the , which selects the middle value after ordering, the disregards intermediate values entirely. For a such as {1, 3, 5, 7, 9}, the minimum is 1 and the maximum is 9, yielding a mid-range of 5, which coincides with the and in this symmetric case. However, its reliance on only two points renders it highly sensitive to outliers; for {1, 2, 3, 4, 100}, the mid-range shifts to 50.5, far from the of 22 and of 3. This constitutes a primary , as extreme values can distort the measure disproportionately, reducing its robustness compared to the or trimmed . The also exhibits low statistical efficiency for normally distributed data, performing worse than the sample in estimating the center over repeated samples. Consequently, it is infrequently used in practice, reserved mainly for preliminary approximations or datasets known to lack outliers and exhibit .

Physics and Engineering

Projectile motion range

The range of a projectile in motion on level ground, neglecting air resistance, is the horizontal distance from the launch point to the impact point at the same . This distance R is derived from the kinematic equations for two-dimensional motion under constant , yielding R = \frac{v_0^2 \sin 2\theta}{[g](/page/G)}, where v_0 is the initial launch speed, \theta is the angle of relative to the , and g \approx 9.8 \, \mathrm{m/s^2} is the near Earth's surface. The derivation assumes uniform velocity v_x = v_0 \cos \theta and parabolic vertical trajectory, with time of flight T = \frac{2 v_0 \sin \theta}{[g](/page/G)}, so R = v_x T./3:_Two-Dimensional_Kinematics/3.3:_Projectile_Motion) This equation holds under idealized conditions: launch and landing at the same height, negligible air drag or other forces, constant g, and no Coriolis effects, which apply well to low-speed, short-range projectiles like thrown objects or light artillery shells. Deviations occur in real scenarios; for instance, air resistance reduces range by dissipating energy, particularly at higher speeds or for elongated projectiles, and requires for precise prediction. The range maximizes when \sin 2\theta = 1, at \theta = 45^\circ, giving R_\mathrm{max} = \frac{v_0^2}{[g](/page/G)}; for other angles, symmetric pairs (e.g., 30° and 60°) yield identical ranges./3:_Two-Dimensional_Kinematics/3.3:_Projectile_Motion) If launch height h exceeds zero, the formula modifies to R = \frac{v_0^2}{[g](/page/G)} \left( \sin 2\theta + 2 \cos^2 \theta \sqrt{\frac{2gh}{v_0^2} + \sin^2 \theta} \right), increasing range and shifting the optimal angle below 45°. Experimental validations, such as tests, confirm the ideal model's accuracy within 5-10% for velocities under standard conditions.

Sensor and signal range

Sensor range in engineering refers to the maximum distance over which a can reliably detect or measure a target or phenomenon, constrained by signal-to-noise ratio thresholds and physical propagation limits. For active sensors like or , this range follows principles derived from the of signal attenuation, where received power diminishes proportionally to the of in monostatic systems due to both transmission and echo paths. Key determinants include transmitted power, antenna gains (transmit and receive), (shorter wavelengths enable higher but greater atmospheric ), target reflectivity or radar cross-section, and system losses such as and minimum detectable signal. Environmental and operational factors further modulate sensor range; for , atmospheric conditions like or introduce , while for ultrasonic sensors, air and affect speed and , often limiting effective detection to tens of meters with operating ranges typically 25-50% below the absolute limit to ensure reliability. Inductive proximity sensors exhibit ranges of millimeters to centimeters, reduced by target material conductivity and size, with standards like DIN EN 50205 specifying reductions for non-ferrous metals. In systems, detection range—often exceeding 100 meters in clear conditions—degrades with low target , in , or misalignment, emphasizing the causal role of return rates over nominal specifications. Signal range, conversely, pertains to the propagation distance of transmitted signals in communication or sensing systems before attenuation renders them unusable, primarily governed by free-space path loss (FSPL) modeled as FSPL = 20 \log_{10}(d) + 20 \log_{10}(f) + 20 \log_{10}(4\pi/c), where d is , f , and c , yielding approximately 6 loss per distance doubling at any frequency. Higher frequencies (e.g., 2.4 GHz vs. 900 MHz) incur steeper losses, necessitating elevated antennas for line-of-sight extensions—such as 9.6 m heights for 8 km at 2.4 GHz—while multipath fading from terrain, buildings, or vegetation can halve effective range via destructive interference. Transmit power and receiver sensitivity set baseline limits, but causal obstructions like ionospheric or tropospheric ducting introduce variability, with empirical models showing 10-15 additional loss over 50 km in urban RF paths at 450 MHz. In practice, and signal ranges overlap in hybrid systems like wireless sensor networks, where detection distances (e.g., 10-100 m for at 2.4 GHz) balance power constraints against , underscoring first-principles trade-offs: amplifying power quadratically extends range but linearly increases and energy costs, while via phased arrays can double by concentrating energy without raw power hikes. These limits stem from electromagnetic wave physics, independent of institutional narratives, with peer-reviewed validations prioritizing measurable over unsubstantiated claims of indefinite extension via unproven technologies.

Frequency and wavelength range

In physics, the frequency range of electromagnetic waves spans from extremely low frequencies around 3 Hz, corresponding to very long radio waves with wavelengths up to 100 km, to gamma rays exceeding 10^{19} Hz with wavelengths below 10^{-11} m. This continuum, known as the , arises from the propagation of oscillating electric and magnetic fields at the , where higher frequencies correlate with shorter wavelengths via the relation \lambda = c / f, with c \approx 3 \times 10^8 m/s in ./23%3A_Electromagnetic_Waves/23.1%3A_The_Electromagnetic_Spectrum) Specific subdivisions include radio waves (3 kHz to 300 GHz, wavelengths 100 km to 1 mm), microwaves (300 MHz to 300 GHz, 1 m to 1 mm), (300 GHz to 400 THz, 1 mm to 700 nm), (400 to 790 THz, 700 to 380 nm), (790 THz to 30 PHz, 380 nm to 10 nm), X-rays (30 PHz to 30 EHz, 10 nm to 0.01 nm), and gamma rays (above 30 EHz, below 0.01 nm). In applications, such as and communications, the range defines the over which a transmits, receives, or processes signals effectively, often limited by capabilities like or filters. For instance, cellular networks operate in bands like 700 MHz to 2.6 GHz for , balancing distance and data , while systems use ranges from 1 GHz (L-band) to 40 GHz (Ka-band) for detection . considerations influence design; longer wavelengths penetrate obstacles better but require larger , as antenna size scales with \lambda / 2 for . systems, including oscilloscopes, specify operational ranges (e.g., up to 1 GHz for models) to ensure accurate capture without . The interplay between frequency and wavelength ranges underpins technologies like , where ranges (0.7–1000 μm) probe molecular vibrations for material analysis, and fiber optics, confined to near- (850–1550 nm) for minimal . Empirical limits stem from quantum effects at high frequencies and practical propagation losses at extremes, with no theoretical upper bound but observational data capping detected gamma rays around 10^{28} Hz from cosmic sources.

Biology and Ecology

Animal home range

The home range of an animal constitutes the spatial domain traversed by an individual during its routine activities, encompassing , , resting, and rearing , rather than a strictly defended area. This contrasts with a , which represents a of the home range that is actively defended against conspecifics through , scent marking, or displays to secure exclusive access to resources. Home ranges often overlap between individuals of the same , facilitating social interactions without necessitating defense, whereas territories minimize such overlap to reduce competition. Estimation of home range size relies on tracking data from methods such as radio telemetry, GPS collars, or direct observations, analyzed via statistical techniques. The minimum convex polygon (MCP) method delineates the range by forming the smallest enclosing all recorded locations, providing a simple but potentially biased estimate that includes unused peripheral areas. (KDE) offers a more probabilistic approach, generating a utilization distribution where isopleths (e.g., 95% for the full range, 50% for core areas) represent the probability of occurrence, better accounting for clustered activity centers. Other advanced models incorporate in movement data or habitat covariates to refine estimates, though no single method universally outperforms others across species or datasets. Home range size varies predictably with intrinsic and extrinsic factors, grounded in resource demands and environmental constraints. Larger-bodied species exhibit proportionally larger ranges due to higher energetic needs and lower population densities, while males typically maintain larger ranges than females to access dispersed mates. Population density inversely correlates with range size, as heightened competition prompts individuals to exploit smaller, more familiar areas to minimize energy expenditure on exploration and maximize resource familiarity. Habitat productivity, , and further modulate sizes: ranges contract in resource-rich environments or wet seasons and expand in sparse or dry conditions; human disturbance often reduces ranges in urban settings by concentrating resources. Empirical examples illustrate these patterns across taxa. Gray squirrels (Sciurus carolinensis) exhibit home ranges of 1.2 to 8 acres (0.005–0.032 km²), scaling with habitat patchiness. Urban coyotes ( latrans) have core home ranges averaging 20.31 km² (50% MCP), smaller than rural counterparts due to anthropogenic food subsidies, while red foxes (Vulpes vulpes) average 3.45 km² under similar conditions. In primates, such as Japanese macaques (Macaca fuscata), seasonal ranges span 11.6–15.4 km², shrinking in spring with peak forage availability. Ecologically, home ranges reflect adaptive spatial strategies for resource acquisition and predator avoidance, underpinning through maintained cognitive maps of dynamic environments. Quantifying them informs by delineating minimum viable patches, assessing , and predicting responses to fragmentation or shifts, as ranges indicate the scale at which animals perceive and respond to heterogeneity.

Ecological tolerance range

The ecological tolerance range, also known as the range of tolerance, refers to the spectrum of environmental conditions under which a given can survive, grow, and reproduce without experiencing physiological stress or mortality. This concept is formalized in , proposed by ecologist Victor Ernest Shelford in 1913, which posits that the distribution, abundance, and success of a are governed by its tolerances to multiple abiotic and factors, each defined by minimum, optimum, and maximum limits. Conditions below the minimum or above the maximum lead to limiting factors that restrict population viability, while the optimum range supports maximal fitness. Tolerance ranges vary by factor and species; for instance, temperature tolerances often delineate fundamental niches, with generalist species exhibiting broader ranges than specialists. species, such as spp., typically endure s from 6°C to 22°C, beyond which metabolic rates disrupt and increase mortality. tolerances are critical in environments; estuarine species like raccoons or certain withstand fluctuations from freshwater (0 ) to near-marine levels (up to 35 ), but exceedances cause osmotic stress and cellular damage. Other key factors include (e.g., most optimal at 6.5–8.0), oxygen levels (minimum dissolved oxygen around 5 mg/L for many vertebrates to avoid ), and sunlight exposure, where deviations induce suboptimal in or behavioral shifts in animals. Individual variation within populations influences effective tolerance ranges, driven by and , such as acclimation to gradual changes. For example, bryophytes like mosses show tolerance limits shaped by moisture and light, with below critical thresholds halting metabolic processes, while excess water promotes fungal overgrowth. Interactions among factors compound effects; high temperatures may narrow tolerance by altering , as observed in aquatic invertebrates where combined and low oxygen reduces survival by 50% or more in lab studies. Broader geographical ranges correlate with wider tolerances, enabling invasion success in non-native habitats, though local can shift limits over generations. In ecological contexts, tolerance ranges underpin habitat suitability and predict responses to perturbations like , where shifting isotherms may push beyond limits, contracting distributions poleward or upslope. Specialists, such as certain with narrow temperature windows (e.g., 5–15°C optima), face heightened risks from exceedances, whereas generalists like maintain viability across wider gradients. Empirical data from field and lab experiments confirm that the narrowest tolerance often dictates overall range limits, emphasizing multifactor integration over single-variable assessments. This framework informs by identifying vulnerability thresholds, as seen in models forecasting 20–30% range reductions for temperature-sensitive taxa under 2°C warming scenarios.

Music and Acoustics

Vocal and instrumental range

denotes the span of pitches, from the lowest to the highest note, that a can produce with sufficient control, volume, and tonal quality to be musically usable. This span is typically measured in semitones or octaves and varies by individual , , and vocal category. For trained singers, a usable range often extends 2 to 3 octaves, though untrained individuals may achieve only 1.5 to 2 octaves reliably. Exceptional cases, such as singer , have documented spans exceeding 10 octaves (from G−5 at 0.189 Hz to G/G♯5 at 807.3 Hz), verified in a recording, but such extremes exceed practical musical application due to limitations at boundaries. Classical voice classifications delineate standard ranges based on (the most comfortable span) and ( shifts). voices extend approximately from to A5; from to F5; (or ) from to D5; from B2 to ; from G2 to ; and from E2 to , per established dictionaries. These categories reflect anatomical differences, with voices generally occupying higher due to shorter, thinner vocal folds averaging 17.5–25 mm in length, compared to 17–25 mm in males but with greater mass, enabling lower fundamentals around 85–180 Hz versus 165–255 Hz. Empirical studies of trained singers confirm overlap in voicing ranges, with sopranos reaching up to 1500–2000 Hz and basses down to 80–100 Hz, though full-range demands breath support and adjustments to avoid strain. Instrumental range parallels as the continuum of pitches an can generate, bounded by its mechanical design, material properties, and performer technique, often extending beyond fundamental tones via harmonics or . For instance, the piano's standard 88-key model spans from A0 (27.5 Hz) to C8 (4186.01 Hz), covering 7 full octaves plus third, limited by length and tension. instruments like the achieve G3 (196 Hz) to about A7 (3520 Hz), roughly 4 octaves, through finger positioning and bowing, while the guitar's yields E2 (82.4 Hz) to (329.6 Hz) on open strings, extendable to higher frets up to about 2–3 additional octaves. instruments such as the produce from F♯3 (185 Hz) to C6 (1046.5 Hz) or higher in the altissimo , relying on lip vibration and valve combinations, with practical limits imposed by airflow and stability. These ranges inform , as composers select instruments to match required pitches while accounting for variations across the span—lower notes often richer in even harmonics, higher ones brighter but prone to instability.

Dynamic range in audio

Dynamic range in audio refers to the measurable difference, expressed in decibels (), between the strongest (loudest) and weakest (quietest) signals that an audio system, recording medium, or human can handle without or unacceptable . This ratio quantifies the span from the —the inherent background hiss or electronic —to the maximum signal level before clipping or overload occurs. In practice, it determines the with which subtle nuances, such as faint decays or ambient details, can be preserved alongside peaks like percussion strikes or orchestral swells. The human auditory system provides a , with a spanning approximately 120 to 130 in the most sensitive bands (around 500 Hz to 6 kHz), from the threshold of hearing near 0 sound pressure level (SPL) to pain thresholds exceeding 120 SPL. This capability allows perception of whispers at about 20-30 SPL alongside jet engines at 140 SPL, though adaptation mechanisms like the stapedius reflex compress perceived range over time to around 90-100 for sustained listening. Audio systems aim to approximate this to convey realism, as insufficient range results in lost detail (quiet sounds masked by noise) or harsh (loud sounds clipped). In analog audio formats, dynamic range is constrained by physical limits: vinyl records typically achieve 60-70 due to groove and surface imperfections, while magnetic tape reaches 70-80 depending on formulation and bias techniques, limited by tape hiss and saturation. , by contrast, derives range from , where each bit provides roughly 6 of resolution; thus, 16-bit depth (standard for CDs) yields a theoretical 96 (20-bit log2(2^16) ≈ 96 ), and 24-bit (common in professional recording) extends to 144 , far exceeding human hearing and enabling headroom for processing without requantization . However, real-world digital range is often lower due to dithering, quantization errors, and converter floors around -120 in high-end analog-to-digital converters. Maintaining adequate during recording and reproduction preserves expressive intent, as music's emotional impact relies on contrasts—piano to forte transitions that evoke tension and release—rather than uniform . Excessive , which narrows range to boost average levels (e.g., for radio play), can induce and diminish perceived depth, though it ensures consistency in noisy environments. In mastering, tools like limiters balance range against commercial standards, but empirical tests show uncompressed recordings with 10-15 dB range retain greater timbral accuracy and spatial imaging on capable systems. Ultimately, the effective range in playback chains—microphones, amplifiers, speakers—is the minimum across components, underscoring the need for matched specifications to avoid bottlenecks.

Geography and Land Use

Mountain range

A mountain range consists of a series or chain of mountains aligned in proximity, typically sharing common geological origins through processes such as tectonic uplift, folding, or volcanic activity. These formations arise predominantly at convergent plate boundaries, where lithospheric plates collide, subjecting the crust to compression that results in crustal thickening, , and the development of fold-thrust belts. For instance, collisional occurs as oceanic basins close and continental crusts converge, producing elongated belts with elevations often exceeding 2,000 meters above surrounding terrain. Key characteristics include significant topographic —defined as the vertical difference between peaks and adjacent lowlands, frequently surpassing 500 to 1,000 meters—and linear alignment due to underlying structural features like faults or anticlines. Mountain ranges exhibit varied morphologies, from sharp, jagged peaks in young orogenic systems to rounded, eroded profiles in older ones, influenced by factors such as uplift rates, by glaciers and rivers, and isostatic rebound. plays a causal role in shaping , as differential exposes resistant rock layers while transporting , thereby enhancing local prominence over geological timescales. Prominent examples include the , the world's longest continental at approximately 7,000 kilometers, extending along South America's western edge due to ongoing of the beneath the . The span about 4,800 kilometers from to , formed by around 70-40 million years ago through flat-slab . These ranges not only demarcate biogeographic barriers but also influence global climate patterns by altering and distribution. Empirical data from seismic and GPS monitoring confirm active deformation in such systems, with uplift rates of millimeters per year sustaining their elevation against erosional downcutting.

Open range grazing

Open range grazing refers to a system of livestock husbandry in which cattle, sheep, or other animals roam freely across unfenced expanses of public or communal land, with no obligation for owners to confine their herds to specific boundaries. This practice historically relied on natural forage and water sources, with herders using seasonal movements to access grass after winter snowmelt or during migrations. In , grazing expanded rapidly from the 1860s onward as settlers introduced large herds to federal public domain lands in states such as , , , and , operating under informal "first come, first served" customs tied to control of water holes. Ranchers grazed millions of without fencing, employing for and ; by the 1880s, an estimated 7.5 million head roamed the open ranges of the Northern Plains alone. Conflicts arose between and sheep operators, culminating in violent episodes like the of 1892 in , where armed ranchers targeted perceived rustlers and smaller competitors, resulting in multiple deaths and federal intervention. The system's viability declined due to , which depleted vegetation and caused , intensified by droughts and severe winters such as the 1886-1887 "Great Die-Up" that killed up to 90% of some herds. The invention of in the 1870s enabled private fencing, fragmenting ranges as homesteaders claimed land under acts like the Homestead Act of 1862, while escalating resource competition prompted calls for . The Taylor Grazing Act, signed into law on June 28, 1934, by President , marked the effective end of unregulated by authorizing the Secretary of the Interior to establish grazing districts on approximately 142 million acres of , issue permits with capacity limits, and impose fees, reducing overall livestock numbers by over 1 million head to curb the "." Under the , grazing transitioned to allocated allotments managed by the newly formed Grazing Service (merged into the in 1946), prioritizing sustainable use through rotational practices and monitoring to prevent degradation. Today, pure persists in limited "fence-out" jurisdictions across Western states including , , , , and , where statutes place the onus on non-livestock owners to erect barriers, though counties may vote to impose fencing requirements on herders. On , which comprise about 155 million acres of grazed , operations occur via permits under 43 CFR Part 4100, with annual adjustments for factors like drought or fire, aiming to maintain ecological health while supporting rural economies. Environmentally, unmanaged open range historically contributed to biodiversity loss and watershed impairment through compaction and invasive species proliferation, but regulated grazing can enhance soil carbon sequestration—rangelands store 50% more organic carbon than global forests—and fire resilience when stock densities align with forage capacity. Critics from conservation groups argue persistent impacts include riparian damage and contamination from waste, yet federal assessments emphasize that compliant practices yield net benefits for sagebrush steppe and grassland ecosystems when monitored.

Technology and Domestic Applications

Kitchen stove range

A kitchen range, also known as a , is an integrated cooking consisting of a for direct heating of cookware and an enclosed for , , or broiling. This design enables simultaneous surface and cavity cooking, distinguishing it from separate cooktops and wall ovens. Typical dimensions range from 30 to 36 inches wide for standard models, with professional styles up to 48 inches. The evolution of kitchen ranges began with open hearths and progressed to enclosed cast-iron wood-burning models in the early , such as the Oberlin Stove patented in 1834, which was compact enough for domestic use and featured a firebox, , and flues for heat circulation. By the mid-, American ranges incorporated ash drawers and warming closets beneath the , improving efficiency over earlier step-stoves. Gas ranges emerged in the late , followed by the first electric range in 1910 by , which offered precise temperature control via resistance heating elements. Ranges are classified by fuel source and installation style. Gas ranges use or flames for rapid, visible heating and precise simmer control, favored by professional cooks, though they emit and other pollutants linked to respiratory risks, with ongoing debate over mitigation via . Electric ranges employ or radiant elements under a smooth ceramic-glass surface for even heating and simpler cleaning, but slower response times. ranges, a subtype of electric, generate via electromagnetic fields that directly excite ferromagnetic cookware, achieving 84-90% compared to 40% for gas and 74% for traditional electric, while remaining cool to touch absent compatible pots, reducing burn and fire hazards. Dual-fuel ranges combine a gas with an electric oven for baking. Freestanding models have exposed sides and storage drawers, while slide-in versions fit flush with for a seamless look. Safety standards, enforced by the U.S. Consumer Product Safety Commission (CPSC), mandate tip-over resistance, automatic shut-off for unattended flames, and surface temperature limits below 194°F (90°C) on exteriors during operation to prevent scalds. Gas models require proper installation to avoid leaks, and all types necessitate clearance from combustibles like curtains. The U.S. Department of Energy finalized efficiency standards in January 2024 for residential cooking tops and ovens, projecting $1.6 billion in utility savings over 30 years through reduced and improved insulation. In , the range market reached $15.81 billion in 2024, driven by demand for and smart features like connectivity for remote monitoring.

Shooting and testing range

A shooting range, also known as a firing range, is a specialized designed for the safe discharge of firearms for purposes such as target practice, skill development, and competitive . These ranges accommodate various weapons including handguns, rifles, shotguns, and sometimes archery equipment, with facilities divided into indoor and outdoor configurations to suit different calibers and user needs. Indoor ranges typically feature controlled environments with bullet traps and systems to manage lead particulates and , while outdoor ranges provide extended distances for long-range rifles and incorporate natural backstops like berms or hills. Safety protocols at shooting ranges universally emphasize four foundational rules derived from organizations like the : treat all firearms as loaded; keep the muzzle pointed in a safe direction downrange; keep fingers off the trigger until ready to fire; and be sure of the target and what lies beyond it. Additional operational standards include eye and hearing protection mandates, prohibitions on or impairing substances, and restrictions to firing only from designated lines at approved targets to prevent ricochets or stray projectiles. Compliance with these rules reduces accident rates, with U.S. firearm-related injuries at ranges remaining low relative to participation volumes exceeding 20 million annual visits. Regulations governing shooting ranges address , environmental impacts, and public safety, varying by but often requiring impenetrable barriers, noise mitigation, and lead remediation plans due to soil and air contamination from spent ammunition. For instance, U.S. facilities must account for projectile containment, solar orientation to avoid glare, and separation from populated areas, with states like defining ranges explicitly for rifles, pistols, and while exempting established operations from nuisance lawsuits. Testing ranges extend beyond recreational use to evaluate weapon performance, reliability, and lethality under controlled conditions, particularly in military contexts. These facilities, such as the U.S. Army's —the largest open-air test site in the Department of Defense—support live-fire trials for missiles, , and hypersonic systems, incorporating instrumentation for trajectory tracking and environmental simulations like extreme temperatures or salt fog exposure. Military testing distinguishes from standard shooting by focusing on empirical metrics like , accuracy at maximum (e.g., up to 1,725 miles for systems like the ), and failure rates in adverse conditions, ensuring causal links between design variables and operational outcomes.

Device operational range

The operational range of a encompasses the defined boundaries of environmental, electrical, and mechanical conditions under which it performs reliably without degradation or failure. These specifications, outlined in manufacturer datasheets, are derived from empirical testing to validate functionality across variables such as , voltage, , and . Exceeding these limits can lead to reduced efficiency, erratic behavior, or permanent damage, as evidenced by in semiconductors beyond rated thresholds. Temperature is a primary , with commercial-grade electronic components typically rated for 0°C to 70°C ambient operation to suit office or consumer environments. variants extend to -40°C to 85°C to accommodate harsher conditions, while specifications reach -55°C to 125°C for reliability in extreme deployments. These ranges account for junction temperatures in active devices like transistors, where heat dissipation influences safe limits; for instance, exceeding 150°C in silicon-based ICs risks and failure. operational ranges often span 0% to 95% non-condensing to prevent or short circuits in enclosures. Electrical operational ranges include input voltage tolerances, where devices must maintain performance within a nominal plus or minus a —such as 5V ±5% for ICs—to avoid under-voltage lockout or overvoltage breakdown. Frequency ranges apply to RF and communication devices, specifying bands like 2.4 GHz ±100 MHz for modules to ensure without . Power consumption limits, often 1-10W for low-power sensors, define sustainable draw under load to prevent thermal overload. Testing protocols, including accelerated life tests at elevated conditions, verify these ranges, with standards like simulating real-world stresses. In devices, operational ranges extend to (e.g., 5-500 Hz at 5g for automotive sensors) and (e.g., 0.5-10 for industrial valves) to guarantee structural . For integrated systems like DC/DC converters, combined ranges—such as -40°C to 85°C at 4.5-5.5V input—ensure cascading failures are minimized. Adherence to these specifications mitigates risks in applications from to , where deviations have caused incidents like fires in portable devices operating outside bounds.

Named Entities

Places named Range

Several small, unincorporated communities in the United States bear the name Range. Geographic records identify six such locales across , , , , , and .
StateDescription
Unincorporated community in Conecuh along Alabama State Route 41; ZIP code 36473 with an estimated population of 24.
Locale within Range Township, Madison .
Neighborhood in Texas near Hardesty.
Unincorporated community in Grant .
Small locale, details limited.
Unincorporated community in Polk near Amery.
One additional place named Range exists in Hesse, Germany, though specific details on its status and location are not widely documented in English-language sources.

People named Range

Heidi Range (born 23 May 1983) is an English best known as a founding member of the girl group from 2001 to 2011, during which the group achieved multiple number-one singles including "About You Now" and "Push the Button." She has also appeared in films such as (2003) and pursued solo ventures including television appearances. M. Athalie Range (November 7, 1915 – November 14, 2006), born Mary Athalie Wilkinson in , Florida, was a Bahamian-American civil rights activist, , and politician who became the first African-American elected to the City Commission in 1965. In 1971, Florida Governor appointed her as the state's first female cabinet-level official, serving as Secretary of the Department of Community Affairs until 1973, where she advanced ordinances on housing and community development. Range Murata (born October 2, 1968, in Osaka, Japan), also known as Renji Murata, is a illustrator and recognized for his dieselpunk-influenced designs blending aesthetics with elements, featured in works such as the Last Exile (2003) and publications like magazine. His contributions include character designs for video games like and art books such as futurelog (2018).

References

  1. [1]
    Range by David Epstein: 9780735214507 - Penguin Random House
    In stock Free deliveryHe discovered that in most fields—especially those that are complex and unpredictable—generalists, not specialists, are primed to excel. Generalists often find ...
  2. [2]
    Range: Why Generalists Triumph in a Specialized world
    David Epstein examined the world's most successful athletes, artists, musicians, inventors, forecasters and scientists. He discovered that in most fields— ...
  3. [3]
    Book Summary: Range by David Epstein - Commoncog
    Aug 19, 2020 · The point is that some athletes start late and succeed. Epstein uses this story as a way of introducing us to his main goal with Range: he ...
  4. [4]
    Range by David Epstein Book Summary - Rick Kettner
    May 13, 2022 · Range by David Epstein is about the many benefits of diverse life experiences. It explains how engaging in a “sampling period” prior to specialization improves ...
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    10 Generalist Insights from Range by David Epstein (Book Summary)
    In Range, David Epstein utilizes a writing style that's primarily focused on sharing a wide variety of stories, interviews, research studies, and anecdotes.
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