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Lora

LoRa is a proprietary long-range, low-power wireless modulation technique developed by Corporation, employing to facilitate efficient, low-data-rate communication over distances exceeding 10 kilometers in rural settings while consuming minimal energy, making it suitable for battery-operated (IoT) devices. Invented in 2009 by Cycleo and acquired by in 2012, LoRa operates in unlicensed sub-gigahertz frequency bands such as 915 MHz in and 868 MHz in , enabling robust signal penetration through obstacles with resistance to interference. As the physical layer for the open LoRaWAN protocol standardized by the LoRa Alliance—a including and over 500 members— it supports scalable deployments for applications including smart metering, , and , where traditional cellular networks prove inefficient due to higher power demands and costs. Despite its proprietary modulation core, which has drawn for potential , LoRa's empirical advantages in range and longevity—often yielding multi-year battery life—have driven widespread adoption, with billions of connected endpoints projected by industry analyses, underscoring its role in enabling cost-effective, decentralized IoT ecosystems without reliance on centralized infrastructure.

Personal names

Given name

Lora is a feminine of Latin origin, derived from laurus, meaning "" or "crowned with ," a symbol of and honor in ancient culture. The name emerged as a variant of or Loretta, with usage documented in English-speaking regions from the 14th century onward, though it gained prominence in the 19th and early 20th centuries. In the United States, Lora entered the top 1,000 names for girls in the late 1800s, peaking at rank 150 in before declining sharply after the mid-20th century; by , it no longer ranked in the top 1,000 according to data. Its usage remains sporadic internationally, appearing in countries like and with low incidence rates. Variants include Lorae, Lorah, and Lorra, often reflecting regional phonetic adaptations. Notable individuals bearing the name include Lora Logic (born Susan , 1960), a British saxophonist and founding member of the band , influential in the late punk scene. The name's enduring but niche appeal ties to its association with classical symbolism rather than modern trends.

Surname

Lora is a surname of origin, functioning as a habitational name derived from locales such as Lora de Estepa or Lora del Río, both situated in the , . This etymology reflects a common pattern in Iberian naming conventions where surnames arise from geographic identifiers associated with ancestral residences or estates. Genetic ancestry data indicates that approximately 47.8% of individuals bearing the surname trace their paternal lineage to and Portuguese roots, with a predominant O-F2415 linked to East Asian and American ancestry in some populations, suggesting historical admixture in colonial contexts. The surname exhibits the highest incidence in the , where it is the most prevalent among global bearers, followed by concentrations in other Hispano- nations; overall, 77% of Lora surname holders reside in the , with 36% in the region specifically. , it ranks as the 5,001st most common surname as of 2010, with 84.2% of bearers identifying as origin and only 11.8% as non-Hispanic white, underscoring its strong association with diaspora communities. Historical records trace the name's presence in the U.S. back to at least 1840, with family concentrations noted in states like and by 1920. Notable individuals include Pedro de Lora, a explorer and navigator who participated in Christopher Columbus's second voyage to the in 1493. Another bearer is Carmelo de Diego Lora, a , canon law , and priest recognized for contributions to ecclesiastical legal scholarship. In modern contexts, Alex Lora (born February 7, 1952) stands out as a Mexican rock musician and the founder and lead singer of the band El Tri, influential in Latin American rock since the 1970s. Alberto Lora Ramos (born October 24, 1987) is a retired footballer who played as a defender, primarily for , accumulating over 100 appearances in .

Geographical locations

Settlements and regions

Several municipalities and settlements bear the name Lora or variants thereof, primarily in , with additional instances in other countries. In , is a in the , , situated on the banks of the River, with a of approximately 19,100 inhabitants. , also in province, is a smaller with an estimated of 891 as of 2023. In , Lora is a located on the Mataquito River within the Licantén commune of , , named after a local Promaucaes tribe. In , Lora Tehsil constitutes an administrative subdivision of in province, encompassing local government structures including a . Smaller settlements named Lora exist elsewhere, such as a village in Dandai Tehsil, , , . Globally, at least 13 places named Lora are recorded across nine countries, including instances in , , and additional sites in .

Natural features

Lora is a natural and harbor in the northwestern part of , integrated into the larger Bay of Kaštela along the Dalmatian coast. This coastal feature consists of sheltered, deep waters enclosed by the bay's -influenced topography, which includes surrounding hills and rocky promontories that mitigate exposure to Adriatic winds and swells. The Bay of Kaštela, encompassing Lora, exemplifies the region's geological profile of submerged poljes and tectonic subsidence, creating a series of interconnected bays with irregular shorelines and submerged valleys dating to the period. Lora's configuration as a narrow, protected stems from this erosional and marine inundation process, fostering a stable anchorage amid the otherwise exposed eastern Adriatic seaboard.

Technology

LoRa (wireless modulation)

is a (CSS) modulation technique originally invented in 2010 by the French startup Cycleo and acquired by Corporation in 2012. It functions as the physical (PHY) layer for low-power wide-area networks (LPWANs), enabling long-range wireless communication with minimal energy consumption, primarily for (IoT) sensor networks. The technique derives from (DSSS) but employs continuously varying frequency chirps to spread the signal across the channel bandwidth, improving receiver sensitivity and robustness over narrowband methods like (FSK). In LoRa , data is encoded using up-s (frequency increasing linearly over the period) or down-s (frequency decreasing), with formed by cyclic shifts of a base chirp sequence. Each carries a number of bits equal to the spreading factor (), where the chirp rate matches the to maintain constant envelope , facilitating efficient power . This CSS approach equates timing acquisition with offset correction at the receiver, simplifying compared to traditional DSSS systems. Core parameters include spreading factor (SF7 to SF12), which sets the ratio of chip rate to symbol rate (2^SF), extending symbol duration for higher SF values to boost processing gain and link margin at the cost of reduced throughput; bandwidth (BW), selectable as 125 kHz, 250 kHz, or 500 kHz to scale the chirp sweep; and coding rate (CR), ranging from 4/5 to 4/8, which adds redundancy for forward error correction via Hamming codes. The resulting bit rate follows R_b = SF \times \frac{BW}{2^{SF}} \times CR, yielding rates from approximately 0.018 kbps (SF12, 125 kHz BW, CR=4/8) to 37.5 kbps (SF7, 500 kHz BW, CR=4/5), with higher SF providing sensitivities down to -148 dBm. Spreading factors are orthogonal, permitting concurrent transmissions across SFs in the same frequency channel without desensing, which supports scalable network capacity. operates in unlicensed sub-1 GHz bands (e.g., 433 MHz, 868 MHz, 915 MHz), achieving rural ranges up to 15 km and urban ranges to 2-5 km under regulatory power limits (typically +14 to +20 dBm transmit power). The modulation's benefits stem from CSS properties, including 90 dB out-of-channel selectivity for rejection, resilience to multipath via rake-like , and tolerance to Doppler shifts up to several km/h, making it suitable for or obstructed environments; it also enables implicit ranging through time-of-flight measurements on timestamps. These attributes yield a 15-20 dB superior to FSK in comparable bandwidths, prioritizing reliability over speed for battery lifetimes exceeding 10 years in low-duty-cycle deployments.

LoRA (machine learning adaptation)

Low-Rank Adaptation () is a parameter-efficient technique for adapting large pre-trained models to downstream tasks by injecting low-rank matrices into the model's layers while keeping the original weights frozen. This approach decomposes the update to a pre-trained weight matrix W as \Delta W = BA, where B is a d \times r matrix, A is an r \times k matrix, and r (the rank) is a small hyperparameter much smaller than d or k, reducing the number of trainable parameters from dk to r(d + k). was developed to address the computational and memory challenges of full large models like , which has 175 billion parameters and requires substantial GPU resources for updates. The method was introduced in a 2021 paper by researchers at , including Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen, titled "LoRA: Low-Rank Adaptation of Large Language Models." Experiments in the paper demonstrated that LoRA achieves performance on par with or better than full on models such as , DeBERTa, , and across tasks including GLUE benchmarks and , while using up to 10,000 times fewer trainable parameters and reducing GPU memory needs by factors of 3 or more. For instance, with LoRA required only 18 MB of trainable parameters compared to 350 GB for full . The technique is implemented by modifying forward passes to include the low-rank updates and training only the decomposition matrices A and B, with A typically initialized to zero to preserve pre-trained behavior initially. LoRA's efficiency stems from the empirical observation that weight updates during often exhibit low intrinsic , allowing low-rank approximations to capture most of the necessary adaptations without or catastrophic . It has been widely adopted in frameworks like Transformers and PEFT libraries for tasks such as instruction tuning, , and personalization of models like and . Variants like QLoRA extend it by quantizing the base model to 4-bit precision, further reducing memory usage to enable on consumer hardware. Key advantages include drastically lower training costs—often 1-3 orders of magnitude in parameters and compute—faster convergence, and the ability to merge adapters post-training for inference without added latency. However, LoRA may underperform full fine-tuning on tasks requiring substantial deviation from the pre-trained distribution, as the fixed low rank limits expressivity; empirical studies show diminishing returns when r is too small or for cross-lingual shifts between dissimilar languages. It also inherits limitations of the base model, such as biases or gaps in pre-training data, without the corrective power of exhaustive parameter updates. Despite these, LoRA's trade-offs favor it for resource-constrained settings, with ongoing research exploring adaptive ranks and mixtures of adapters to mitigate constraints.

Other uses

Typography and design

Lora is a family designed primarily by type designer Olga Karpushina, with contributions from Alexei Vanyashin, and released in 2011 by the type foundry Cyreal. It draws inspiration from calligraphic forms, featuring moderate contrast between thick and thin strokes that lends a balanced, contemporary appearance suitable for extended reading in body text. The design emphasizes readability through subtle variations in stroke width and terminal shapes, avoiding the of more dramatic serifs while incorporating fluid, painterly curves reminiscent of . Its italics exhibit a pronounced calligraphic slant and flourish, enhancing expressiveness without compromising legibility, which distinguishes from rigidly geometric serifs. The family supports Latin and Cyrillic scripts, with a version later developed to allow flexible weight adjustments across a range from thin to black. In typographic applications, Lora's moderate and open counters promote clear hierarchy in print and , performing well at small sizes due to its even spacing and avoidance of overly condensed proportions. Distributed freely via under an , it has been adopted for web and editorial uses where a classic yet modern is desired, often paired with sans-serifs like for contrast.

Biology and notable animals

The Yellow-shouldered Amazon (Amazona barbadensis), locally known as the Lora in regions such as , is a medium-sized endemic to arid coastal zones of northern and the Caribbean island of . This species inhabits dry deciduous forests, thorn scrub, and mangroves, adapting to semi-arid environments as the only member of its restricted to such habitats. Adults measure about 33 cm in length and weigh approximately 270 g, with predominantly green accented by yellow on the crown, shoulders, and outer tail feathers, alongside a whitish forehead and blue eye-ring. Lor as are primarily frugivorous and granivorous, consuming seeds, fruits, flowers, and cacti, supplemented occasionally by ; they forage in flocks during the day and roost communally in tall trees, sometimes numbering up to 700 individuals. Breeding occurs in tree cavities or abandoned holes, with clutches of 2–4 eggs laid from to in , and incubation lasting around 26 days. The faces severe threats from habitat degradation, nest predation by rats and cats, and illegal pet trade, resulting in an estimated wild population of 2,500–9,999 individuals and a classification of Endangered by the IUCN as of 2024. measures, including nest protection, artificial nest provision, and reintroduction programs—such as the release of captive-raised individuals into Aruba's wilds on January 11, 2024—have shown success in bolstering local populations on and . Another biological entity termed Lora is the parrot snake (Leptophis ahaetulla), a slender colubrid species distributed from Mexico through Central America to northern South America. This diurnal, arboreal snake reaches lengths of up to 180 cm, exhibiting a bright green dorsum with yellow lateral stripes and mildly venomous rear fangs used to subdue prey. It preys opportunistically on arboreal amphibians, lizards, bird eggs, nestlings, and small mammals, employing constriction alongside envenomation; females are oviparous, laying clutches whose size varies but has been documented as 3–5 eggs in some populations. No highly notable individual animals named Lora have been widely documented beyond these species' ecological roles.

References

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