cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.wyjskp
title: Occurrence Download

description: A dataset containing 23 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 GBIF_WITHIN('POLYGON((13.31871 54.07021,13.81063 54.07021,13.81063 54.33994,13.31871 54.33994,13.31871 54.07021))', occurrence.decimallatitude, occurrence.decimallongitude) = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND (CAST(occurrence.taxonkey AS INTEGER) = 2863967 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 2863967 OR CAST(occurrence.kingdomkey AS INTEGER) = 2863967 OR CAST(occurrence.phylumkey AS INTEGER) = 2863967 OR CAST(occurrence.classkey AS INTEGER) = 2863967 OR CAST(occurrence.orderkey AS INTEGER) = 2863967 OR CAST(occurrence.familykey AS INTEGER) = 2863967 OR CAST(occurrence.genuskey AS INTEGER) = 2863967 OR CAST(occurrence.specieskey AS INTEGER) = 2863967)
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 23 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020619-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hz7fa6
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Andrena vernalis"
 ]
}

 The dataset includes 76 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020658-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zr5sty
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Happywhale - Polar bear in North Atlantic Ocean"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020660-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.34bu42
title: Occurrence Download

description: A dataset containing 729 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((11.73848775360558 50.960418606966584,13.121880060905012 50.960418606966584,13.121880060905012 52.343810914266015,11.73848775360558 52.343810914266015,11.73848775360558 50.960418606966584))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Impatiens glandulifera"
 ]
}

 The dataset includes 729 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020656-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75x4cv
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Andrena runcinatae"
 ]
}

 The dataset includes 87 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020657-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tgvbu2
title: Occurrence Download

description: A dataset containing 830 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lynx pardinus)",
 "OccurrenceStatus is one of (Present)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "Year is greater than or equal to 1970"
 ]
}

 The dataset includes 830 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020654-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6qzhe2
title: Occurrence Download

description: A dataset containing 154 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Andrena parnassiae"
 ]
}

 The dataset includes 154 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020655-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18301124
title: SUN'IY INTELLEKT TEXNOLOGIYALARINING FARMASEVTIK TADQIQOTLARDAGI O'RNI VA ISTIQBOLLARI

description: Mazkur maqolada sun’iy intellekt texnologiyalarining farmasevtik tadqiqotlardagi o‘rni va ahamiyati ilmiy-nazariy jihatdan tahlil qilindi. Tadqiqot davomida mashinaviy o‘rganish, chuqur o‘rganish hamda katta ma’lumotlar tahlili asosida dori vositalarini ishlab chiqish jarayonlarini optimallashtirish imkoniyatlari o‘rganildi. Olingan natijalar sun’iy intellekt texnologiyalarining biologik faol birikmalarni aniqlash, molekulyar modellashtirish, klinik sinovlarni rejalashtirish va individual tibbiyot konsepsiyasini rivojlantirishdagi samaradorligini ko‘rsatdi. Shuningdek, mazkur texnologiyalarni qo‘llashda uchraydigan asosiy muammolar — ma’lumotlar sifati, etik va huquqiy masalalar muhokama qilindi. Tadqiqot natijalari sun’iy intellekt farmasevtika sohasida istiqbolli va strategik yo‘nalish ekanligini asoslab beradi
DOI: 10.5281/zenodo.18301123
title: SUN'IY INTELLEKT TEXNOLOGIYALARINING FARMASEVTIK TADQIQOTLARDAGI O'RNI VA ISTIQBOLLARI

description: Mazkur maqolada sun’iy intellekt texnologiyalarining farmasevtik tadqiqotlardagi o‘rni va ahamiyati ilmiy-nazariy jihatdan tahlil qilindi. Tadqiqot davomida mashinaviy o‘rganish, chuqur o‘rganish hamda katta ma’lumotlar tahlili asosida dori vositalarini ishlab chiqish jarayonlarini optimallashtirish imkoniyatlari o‘rganildi. Olingan natijalar sun’iy intellekt texnologiyalarining biologik faol birikmalarni aniqlash, molekulyar modellashtirish, klinik sinovlarni rejalashtirish va individual tibbiyot konsepsiyasini rivojlantirishdagi samaradorligini ko‘rsatdi. Shuningdek, mazkur texnologiyalarni qo‘llashda uchraydigan asosiy muammolar — ma’lumotlar sifati, etik va huquqiy masalalar muhokama qilindi. Tadqiqot natijalari sun’iy intellekt farmasevtika sohasida istiqbolli va strategik yo‘nalish ekanligini asoslab beradi
DOI: 10.15468/dl.upmjmt
title: Occurrence Download

description: A dataset containing 520 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brunei Darussalam",
 "OccurrenceStatus is Present",
 "TaxonKey is Hymenoptera"
 ]
}

 The dataset includes 520 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020661-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pv7bm6
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plesiopelma semiaurantiacum"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020662-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7c2u6f
title: Occurrence Download

description: A dataset containing 2392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.09571 5.61038,-75.12067 5.60862,-75.13201 5.58717,-75.12987 5.56571,-75.11676 5.5622,-75.09382 5.56295,-75.08386 5.57951,-75.08499 5.6041,-75.08953 5.60937,-75.09571 5.61038))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2392 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020663-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18299982
title: A Tree Search-Based Heuristic for the Three-Dimensional Single Container Loading Problem

description: A Tree Search‑Based Heuristic for the Three‑Dimensional Single Container Loading Problem

This repository contains all the research data. You can find a brief description of each file below.



sclp_app_docker.tar.gz: Docker image (tarball) containing the SCLP application environment, ready for deployment and reproducible experiments. You can find how to run it in the README in 3d_sclp_source_code.

lucasguesserts_masters_thesis.pdf: PDF version of Lucas Guesser’s master’s thesis, providing background, methodology, and results related to the research. Note that there were some change to the name of the heuristics from the dissertation to the paper published.

3d_sclp_source_code.zip: Source code of the heuristic proposed.



This code is also available in https://github.com/lucasguesserts/sclp-heuristic



araya_et_al_2017_source_code.zip: Original source code accompanying the 2017 Araya et al. study, used here for baseline comparisons.



Araya et al. have their repository with the code: https://github.com/rilianx/Metasolver

The authors have their fork of that repository. We hope ours is easier to compile: https://github.com/lucasguesserts/Metasolver



experimental_results.zip: Archive of all raw experimental output files and analyses generated during the study.

instance_generator_bischoff_and_ratcliff_1995.zip: A generator of the Bischoff & Ratcliff (1995) benchmark instances.

instances_1995_bischoff_and_ratcliff_and_1999_davies_and_bischoff.zip: The benchmark instances from the 1995 Bischoff/Ratcliff and 1999 Davies/Bischoff datasets.



In addition to the files in our file format, we also provide the files provided by other authors.



lucasguesser_master_thesis.zip: Full archive of Lucas Guesser’s master thesis source files (LaTeX, figures, bibliography).



It can also be found in https://www.repositorio.unicamp.br/Busca/Download?codigoArquivo=582099



packing-visualizer.zip: Web-based tool to visualize the packings produced by the proposed heuristic.



This code is also available in https://github.com/lucasguesserts/packing-visualizer



scripts.zip: Scripts (data preprocessing, post‑processing, and automation) used throughout the experiments. It contains:



solve: a script that automates the whole process of executing the heuristic in parallel with many different configurations.

tuning/: scripts and configurations used to run irace.

figure_tools: scripts used to create the figures of the paper.
DOI: 10.5281/zenodo.18299983
title: A Tree Search-Based Heuristic for the Three-Dimensional Single Container Loading Problem

description: A Tree Search‑Based Heuristic for the Three‑Dimensional Single Container Loading Problem

This repository contains all the research data. You can find a brief description of each file below.



sclp_app_docker.tar.gz: Docker image (tarball) containing the SCLP application environment, ready for deployment and reproducible experiments. You can find how to run it in the README in 3d_sclp_source_code.

lucasguesserts_masters_thesis.pdf: PDF version of Lucas Guesser’s master’s thesis, providing background, methodology, and results related to the research. Note that there were some change to the name of the heuristics from the dissertation to the paper published.

3d_sclp_source_code.zip: Source code of the heuristic proposed.



This code is also available in https://github.com/lucasguesserts/sclp-heuristic



araya_et_al_2017_source_code.zip: Original source code accompanying the 2017 Araya et al. study, used here for baseline comparisons.



Araya et al. have their repository with the code: https://github.com/rilianx/Metasolver

The authors have their fork of that repository. We hope ours is easier to compile: https://github.com/lucasguesserts/Metasolver



experimental_results.zip: Archive of all raw experimental output files and analyses generated during the study.

instance_generator_bischoff_and_ratcliff_1995.zip: A generator of the Bischoff & Ratcliff (1995) benchmark instances.

instances_1995_bischoff_and_ratcliff_and_1999_davies_and_bischoff.zip: The benchmark instances from the 1995 Bischoff/Ratcliff and 1999 Davies/Bischoff datasets.



In addition to the files in our file format, we also provide the files provided by other authors.



lucasguesser_master_thesis.zip: Full archive of Lucas Guesser’s master thesis source files (LaTeX, figures, bibliography).



It can also be found in https://www.repositorio.unicamp.br/Busca/Download?codigoArquivo=582099



packing-visualizer.zip: Web-based tool to visualize the packings produced by the proposed heuristic.



This code is also available in https://github.com/lucasguesserts/packing-visualizer



scripts.zip: Scripts (data preprocessing, post‑processing, and automation) used throughout the experiments. It contains:



solve: a script that automates the whole process of executing the heuristic in parallel with many different configurations.

tuning/: scripts and configurations used to run irace.

figure_tools: scripts used to create the figures of the paper.
DOI: 10.5281/zenodo.18300039
title: Raport końcowy lampy studyjnej Quadralite

description: Raport końcowy podsumowujący badania nad nowymi produktami marki Quadralite. Elementy nad którymi prowadzono prace obejmowały kilka kluczowych cech: charakterystyka światła, czujność nadajnika radiowego.
DOI: 10.5281/zenodo.18300040
title: Raport końcowy lampy studyjnej Quadralite

description: Raport końcowy podsumowujący badania nad nowymi produktami marki Quadralite. Elementy nad którymi prowadzono prace obejmowały kilka kluczowych cech: charakterystyka światła, czujność nadajnika radiowego.
DOI: 10.14272/dummy.56
title: 8.6 wt.% Ni/Al2O3

description: This is a physical chemical entity[CHEBI_24431] which was not directly associated with a molecule[CHEBI_25367].
 The physical chemical entity[CHEBI_24431] can be described by the molecular mass descriptor [cheminf_000088]: .
 
 The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]:
 
 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-57257

 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]:
 Melting point descriptor[CHEMINF_000256]: 
 Boiling point descriptor[CHEMINF_000257]: 
 Refractive index descriptor[CHEMINF_000253]:

 The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]:
 
 OBI:0000094 | material processing (preparative method)
 
 The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: 

 Used ontologies:
 CHEBI - Chemical Entities of Biological Interest
 CHEMINF - chemical information ontology (information entities about chemical entities)
 CHMO - Chemical Methods Ontology
 OBI - Ontology for Biomedical Investigations
DOI: 10.14272/dummy/obi0000094
title: material processing (preparative method) ()

description: dataset for material processing (preparative method)
DOI: 10.34808/2xab-4969
title: Density, air content and open porosity results

description: Results of density, air content and open porosity of M0, M20B and M20M mixtures. Sample designation in the Excel file is in line with sample designation in the manuscript associated with dataset.
M0 - reference sampleM20B - 20% of aggregate replaced with brick aggregateM20M - 20% of aggregate replaced with magnetite aggregate
DOI: 10.5281/zenodo.18300999
title: ViralMultiNet SARS-CoV-2 ORF-level Functional Classification Dataset

description: This dataset supports the publication "ViralMultiNet: A Structure-Aware Multimodal Framework for Viral Genome Classification" in GigaScience (2025).

The dataset contains 66,011 processed SARS-CoV-2 ORF sequences (300-900 bp) with functional classifications derived from wastewater metagenomic surveillance data.

Dataset Contents:- Balanced training (47,091), validation (9,417), and test (9,503) splits- Four functional classes: Enzymatic, Structural, Transport, Other- Pre-computed BERT annotation embeddings (768-dimensional)- K-mer to protein structure residue mappings- PDB structure files (6VXX, 7BV2)- High-attention k-mer regions (4-7-mer scales)

Source code: https://github.com/DAVE-HUB-11/ViralMultiNet-gigascienceRaw data: NCBI BioProject PRJNA1251232License: MITContact: xwx@guet.edu.cn
DOI: 10.5281/zenodo.18301000
title: ViralMultiNet SARS-CoV-2 ORF-level Functional Classification Dataset

description: This dataset supports the publication "ViralMultiNet: A Structure-Aware Multimodal Framework for Viral Genome Classification" in GigaScience (2025).

The dataset contains 66,011 processed SARS-CoV-2 ORF sequences (300-900 bp) with functional classifications derived from wastewater metagenomic surveillance data.

Dataset Contents:- Balanced training (47,091), validation (9,417), and test (9,503) splits- Four functional classes: Enzymatic, Structural, Transport, Other- Pre-computed BERT annotation embeddings (768-dimensional)- K-mer to protein structure residue mappings- PDB structure files (6VXX, 7BV2)- High-attention k-mer regions (4-7-mer scales)

Source code: https://github.com/DAVE-HUB-11/ViralMultiNet-gigascienceRaw data: NCBI BioProject PRJNA1251232License: MITContact: xwx@guet.edu.cn
DOI: 10.21227/gqpf-8k41
title: "JSPinstances"

description: "INSTANCES"
DOI: 10.15468/dl.g8u69g
title: Occurrence Download

description: A dataset containing 569 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Long-term monitoring of the relative density in the Iberian lynx (Lynx pardinus) with track counts in Doñana National Park 2007-2022"
 ]
}

 The dataset includes 569 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020666-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tr3kjm
title: Occurrence Download

description: A dataset containing 4114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Araucaria araucana"
 ]
}

 The dataset includes 4114 records from 146 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020668-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18301141
title: О СОЗДАНИИ АВТОМАТИЗИРОВАННОГО МОНИТОРИНГА ПОДЗЕМНОЙ ГИДРОСФЕРЫ

description: x
DOI: 10.5281/zenodo.18301142
title: О СОЗДАНИИ АВТОМАТИЗИРОВАННОГО МОНИТОРИНГА ПОДЗЕМНОЙ ГИДРОСФЕРЫ

description: x
DOI: 10.15468/dl.tyd23h
title: Occurrence Download

description: A dataset containing 2030 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Clinopodium alpinum, Satureja alpina, Calamintha alpina, Acinos alpinus)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 2030 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020667-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/k5ny-yq43
title: Rheological properties of cement mortar with mixed aggregate

description: Rheological data of cement mortars containing diffrent aggregate composition using Anton Paar MCR 72  stress-imposed rheometer, equipped with vane geometry.
Specimen designation is associated with samples designation in the associated manuscript.
SYS - static yield stress
DYS - Thixotrophy
THX - recovery rate
M0 - reference sampleM20B - 20% of aggregate replaced with brick aggregateM20M - 20% of aggregate replaced with magnetite aggregate
DOI: 10.34808/k8nm-bm47
title: Green strength (buildability performance) of concretes containing mixed aggregate

description: Raw data for determination of buildability (green strength) properties of concrete mixes determined by squeezing test using QuantumX MX840B with CATMAN-EASY software, determined after 30, 45, 60 and 75 minutes. Values present force and two displacement measurements by LVDT. Specimen designation is associated with samples designation in the associated manuscript.
DOI: 10.5281/zenodo.18301169
title: КЛИНИКА И ТЕЧЕНИЕ ОСТРОГО СРЕДНЕГО ОТИТА У ДЕТЕЙ НА ФОНЕ ХРОНИЧЕСКОГО ГЕПАТИТА В

description: Ушбу изланиш мақсади  сурункали вирусли гепатит В  билан зарарланган болаларда ўткир ўрта отитнинг клиникаси ва кечишини ўрганишдан иборат. Кўриниб турибдики, сурункали вирусли гепатит В  фонида ўткир ўрта отит 14 ёшгача булган  60 та болаларда кузатилаяпти. Шулардан 32 таси ўғил болаларни, 28 таси қиз болаларни ташкил этаяпти. Кузатувлар натижаси шуни кўрсатдики, сурункали вирусли гепатит В  билан касалланган болаларда ўткир ўрта отитнинг қуйидаги клиник симптомлари юқори фоизларда кузатилди: қулоқда оғриқ, қулоқдан йиринг оқиши, тана ҳароратининг кўтарилиши, токсикоз ва эксикоз ҳолатлари.  Бизнинг назаримизда сурункали вирусли гепатит В  фонида ривожланган ўткир ўрта отитнинг клиник кўриниши, биринчи навбатда сурункали гепатит-вирусининг гепатоцитлар ва иммун ҳужайраларининг зарарлаш биологик хусусияти, ҳамда бола организмининг анатомо-физиологик хусусиятига боғлиқ. Хулоса қилиб шуни айтиш керакки, сурункали вирусли гепатит В  фонида ривожланган ўткир ўрта отитнинг клиникаси ва кечиши, сурункали вирусли гепатит В  билан зарарланмаган болаларда бир хилда кечади. Шу сабабли, шифокорлар ўткир ўрта отитни антибактериал даволашда иммунокомпонентли болаларни даволашдагидек тавсия беришлар лозим.