cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18217079
title: INSON RUHIYATINI IFODALOVCHI BIRLIKLARNING MILLIY-MADANIY XUSUSIYATLARI

description: Mazkur ilmiy tadqiqot inson ruhiyatini ifodalovchi til birliklarining milliy-madaniy xususiyatlarini chuqur va har tomonlama o‘rganishga bag‘ishlangan. Tadqiqotda insonning ichki kechinmalari, hissiy holatlari, ruhiy jarayonlari va psixologik holatini ifodalovchi leksik birliklar, frazeologizmlar, metaforalar hamda maqol va matallarning til tizimidagi o‘rni va semantik xususiyatlari tahlil qilinadi. Ushbu birliklarning shakllanishi va rivojlanishida xalqning tarixiy taraqqiyoti, an’ana va urf-odatlari, diniy e’tiqodlari, milliy tafakkuri hamda madaniy qadriyatlarining ta’siri alohida e’tiborga olinadi. Jarayonida til va madaniyatning uzviy bog‘liqligi, inson ruhiyati bilan bog‘liq tushunchalarning milliy dunyoqarash asosida til vositasida ifodalanishi yoritib beriladi. Inson ruhiyatini ifodalovchi birliklarning emotsional-ekspressiv bo‘yoqlari, baholovchanlik xususiyatlari hamda ramziy ma’nolari lingvomadaniy va psixolingvistik yondashuvlar asosida tahlil qilinadi. Shuningdek, ushbu birliklarning turli tillarda ifodalanishidagi umumiylik va farqli jihatlar qiyosiy-tavsifiy metodlar orqali aniqlanadi. Tadqiqot natijalari inson ruhiyatining til orqali milliy-madaniy talqinini ochib berishga xizmat qiladi hamda lingvokulturologiya, kognitiv tilshunoslik, psixolingvistika va tarjima nazariyasi kabi sohalarning rivojiga muhim ilmiy-amaliy hissa qo‘shadi.
DOI: 10.5281/zenodo.18217091
title: PEDAGOGICAL SIGNIFICANCE OF THE 4C MODEL IN ENSURING CONTINUITY AND DEVELOPING COMPETENCIES IN THE GENERAL EDUCATION SYSTEM

description: This article examines the pedagogical significance of the 4C model - Critical Thinking, Creativity, Communication, and Collaboration - in ensuring educational continuity and developing key competencies in general education. From a general pedagogy perspective, the study analyzes how integrating the 4C model supports coherence in educational content, teaching methods, and learning outcomes across different educational stages. The research is based on a competency-based approach and a comparative analysis of international educational practices and contemporary pedagogical theories. Qualitative methods, including theoretical analysis and synthesis, were employed. The findings demonstrate that systematic implementation of the 4C model enhances learners’ cognitive, social, and communicative competencies and strengthens educational continuity within modern educational reforms.
DOI: 10.5281/zenodo.18217090
title: PEDAGOGICAL SIGNIFICANCE OF THE 4C MODEL IN ENSURING CONTINUITY AND DEVELOPING COMPETENCIES IN THE GENERAL EDUCATION SYSTEM

description: This article examines the pedagogical significance of the 4C model - Critical Thinking, Creativity, Communication, and Collaboration - in ensuring educational continuity and developing key competencies in general education. From a general pedagogy perspective, the study analyzes how integrating the 4C model supports coherence in educational content, teaching methods, and learning outcomes across different educational stages. The research is based on a competency-based approach and a comparative analysis of international educational practices and contemporary pedagogical theories. Qualitative methods, including theoretical analysis and synthesis, were employed. The findings demonstrate that systematic implementation of the 4C model enhances learners’ cognitive, social, and communicative competencies and strengthens educational continuity within modern educational reforms.
DOI: 10.15468/dl.vxpwhx
title: Occurrence Download

description: A dataset containing 2467 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((111.357 21.461,115.422 21.461,115.422 24.392,111.357 24.392,111.357 21.461))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Centropus bengalensis"
 ]
}

 The dataset includes 2467 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003278-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18217099
title: SUN'IY INTELLEKT TIZIMLARI VA LMS MODELLARINI INTEGRATSIYALASH ASOSIDA O'QUV JARAYONINI AVTOMATLASHTIRISH PLATFORMASINI YARATISH

description: Mazkur maqolada sun’iy intellekt tizimlari va Learning Management System (LMS) modellarini integratsiyalash asosida o‘quv jarayonini avtomatlashtirish platformasini yaratish masalalari ilmiy-nazariy va amaliy jihatdan tahlil qilingan. Tadqiqotda zamonaviy ta’lim tizimida raqamli transformatsiyaning ahamiyati, an’anaviy LMS platformalarining cheklovlari hamda ularni sun’iy intellekt texnologiyalari bilan boyitish zarurati asoslab berilgan. Shuningdek, avtomatlashtirilgan o‘quv platformasining arxitekturasi, funksional imkoniyatlari, adaptiv baholash mexanizmlari, shaxsiylashtirilgan ta’lim yo‘nalishlarini shakllantirish hamda ta’lim sifatini oshirishdagi o‘rni yoritilgan. Maqolada sun’iy intellekt asosida ma’lumotlarni tahlil qilish, prognozlash va qaror qabul qilish jarayonlarining ta’lim samaradorligiga ta’siri ko‘rsatib berilgan. Tadqiqot natijalari raqamli va intellektual ta’lim muhitini rivojlantirish, o‘quv jarayonlarini avtomatlashtirish hamda ta’lim boshqaruvini takomillashtirishda ilmiy-amaliy ahamiyatga ega.
DOI: 10.5281/zenodo.18217098
title: SUN'IY INTELLEKT TIZIMLARI VA LMS MODELLARINI INTEGRATSIYALASH ASOSIDA O'QUV JARAYONINI AVTOMATLASHTIRISH PLATFORMASINI YARATISH

description: Mazkur maqolada sun’iy intellekt tizimlari va Learning Management System (LMS) modellarini integratsiyalash asosida o‘quv jarayonini avtomatlashtirish platformasini yaratish masalalari ilmiy-nazariy va amaliy jihatdan tahlil qilingan. Tadqiqotda zamonaviy ta’lim tizimida raqamli transformatsiyaning ahamiyati, an’anaviy LMS platformalarining cheklovlari hamda ularni sun’iy intellekt texnologiyalari bilan boyitish zarurati asoslab berilgan. Shuningdek, avtomatlashtirilgan o‘quv platformasining arxitekturasi, funksional imkoniyatlari, adaptiv baholash mexanizmlari, shaxsiylashtirilgan ta’lim yo‘nalishlarini shakllantirish hamda ta’lim sifatini oshirishdagi o‘rni yoritilgan. Maqolada sun’iy intellekt asosida ma’lumotlarni tahlil qilish, prognozlash va qaror qabul qilish jarayonlarining ta’lim samaradorligiga ta’siri ko‘rsatib berilgan. Tadqiqot natijalari raqamli va intellektual ta’lim muhitini rivojlantirish, o‘quv jarayonlarini avtomatlashtirish hamda ta’lim boshqaruvini takomillashtirishda ilmiy-amaliy ahamiyatga ega.
DOI: 10.5281/zenodo.18216217
title: CEF_Bundle1_CanonOverview

description: This bundle provides the **official entry point** to the Core Emotion Framework (CEF).  It contains the two documents that define the structure, dependencies, and publication map of the entire CEF canon:

- **TS‑0 — Canon Overview Document**  - **Phase‑4 Master Index**

Together, these documents explain:

- what the CEF is  - how the canon is organized  - how the conceptual, computational, and semantic layers interlock  - how to navigate the full TS‑Series and EL‑Series  - how Phase 4 was completed  

This bundle is the authoritative front door to the CEF.

---

## **2. Contents of This Bundle**

```01_Abstract.pdf02_CEF_Introduction.pdf03_TS0_CanonOverview.pdf04_Phase4_MasterIndex.pdf05_README.txt```

### **01_Abstract.pdf**  A concise summary of the CEF and the purpose of this bundle.

### **02_CEF_Introduction.pdf**  A short, accessible introduction to the CEF, its layers, and how to navigate the canon.

### **03_TS0_CanonOverview.pdf**  The canonical overview of the entire CEF, including structure, dependencies, and conceptual map.

### **04_Phase4_MasterIndex.pdf**  A complete inventory of all Phase‑4 outputs, including the computational ontology (TS‑18), reasoning engine (TS‑19), knowledge graph architecture (TS‑20), population pipeline (TS‑21), and the EL‑1 v1.0 lexicon.

### **05_README.txt**  This file.

---

## **3. How to Cite This Bundle**

**Recommended citation:**

Bulgaria, J. (2026). *Core Emotion Framework (CEF): Canon Overview Bundle (Version 1.0).* OptimizeYourCapabilities.com. CC‑BY 4.0. DOI: 10.5281/zenodo.18216217.

---

## **4. Related Bundles**

This bundle is part of a three‑bundle publication set:

- **Bundle 1:** Canon Overview (this bundle)  - **Bundle 2:** Computational Architecture (TS‑18 → TS‑21)  - **Bundle 3:** EL‑1 Lexicon (500‑term emotional lexicon)

Each bundle is published separately and receives its own DOI.
DOI: 10.5281/zenodo.18216216
title: CEF_Bundle1_CanonOverview

description: This bundle provides the **official entry point** to the Core Emotion Framework (CEF).  It contains the two documents that define the structure, dependencies, and publication map of the entire CEF canon:

- **TS‑0 — Canon Overview Document**  - **Phase‑4 Master Index**

Together, these documents explain:

- what the CEF is  - how the canon is organized  - how the conceptual, computational, and semantic layers interlock  - how to navigate the full TS‑Series and EL‑Series  - how Phase 4 was completed  

This bundle is the authoritative front door to the CEF.

---

## **2. Contents of This Bundle**

```01_Abstract.pdf02_CEF_Introduction.pdf03_TS0_CanonOverview.pdf04_Phase4_MasterIndex.pdf05_README.txt```

### **01_Abstract.pdf**  A concise summary of the CEF and the purpose of this bundle.

### **02_CEF_Introduction.pdf**  A short, accessible introduction to the CEF, its layers, and how to navigate the canon.

### **03_TS0_CanonOverview.pdf**  The canonical overview of the entire CEF, including structure, dependencies, and conceptual map.

### **04_Phase4_MasterIndex.pdf**  A complete inventory of all Phase‑4 outputs, including the computational ontology (TS‑18), reasoning engine (TS‑19), knowledge graph architecture (TS‑20), population pipeline (TS‑21), and the EL‑1 v1.0 lexicon.

### **05_README.txt**  This file.

---

## **3. How to Cite This Bundle**

**Recommended citation:**

Bulgaria, J. (2026). *Core Emotion Framework (CEF): Canon Overview Bundle (Version 1.0).* OptimizeYourCapabilities.com. CC‑BY 4.0. DOI: 10.5281/zenodo.18216217.

---

## **4. Related Bundles**

This bundle is part of a three‑bundle publication set:

- **Bundle 1:** Canon Overview (this bundle)  - **Bundle 2:** Computational Architecture (TS‑18 → TS‑21)  - **Bundle 3:** EL‑1 Lexicon (500‑term emotional lexicon)

Each bundle is published separately and receives its own DOI.
DOI: 10.5281/zenodo.18217028
title: Data AI-Supported Writing in Education: A Large-Scale Review and a Focused Synthesis of Secondary School Research

description: AI-Supported Writing in Education: A Large-Scale Review and a Focused Synthesis of Secondary School Research

2015-25 130 ai writing secondary SON.xlsx is 130 WoS Article with abstracts that are hits of inquiry with AI, writing, secondary keywords.

 education 1.xls and education 2.xls are 1542 WoS Article with abstracts that are hits of inquiry with AI, writing, education keywords.
DOI: 10.5281/zenodo.18217029
title: Data AI-Supported Writing in Education: A Large-Scale Review and a Focused Synthesis of Secondary School Research

description: AI-Supported Writing in Education: A Large-Scale Review and a Focused Synthesis of Secondary School Research

2015-25 130 ai writing secondary SON.xlsx is 130 WoS Article with abstracts that are hits of inquiry with AI, writing, secondary keywords.

 education 1.xls and education 2.xls are 1542 WoS Article with abstracts that are hits of inquiry with AI, writing, education keywords.
DOI: 10.5281/zenodo.18213062
title: Processed datasets for DANST enables cell-type deconvolution in spatial transcriptomics using deep domain adversarial neural networks

description: This record contains the processed spatial transcriptomics and scRNA-seq datasets used for benchmarking and validating the DANST deconvolution framework, as described in the associated paper.
DOI: 10.5281/zenodo.18213061
title: Processed datasets for DANST enables cell-type deconvolution in spatial transcriptomics using deep domain adversarial neural networks

description: This record contains the processed spatial transcriptomics and scRNA-seq datasets used for benchmarking and validating the DANST deconvolution framework, as described in the associated paper.
DOI: 10.6084/m9.figshare.28226687
title: Raw data files of the crown rot projects

description: These are raw sequencing files for the Plant and Soil paper, titled "Crop microbiome responses to pathogen colonisation regulate the host plant defence".
DOI: 10.6084/m9.figshare.28226687.v1
title: Raw data files of the crown rot projects

description: These are raw sequencing files for the Plant and Soil paper, titled "Crop microbiome responses to pathogen colonisation regulate the host plant defence".
DOI: 10.48668/2h85os
title: testing 23/12/2025

description: testing
DOI: 10.48668/2h85os/aj5dz9
title: whale.jpg

description: :unav
DOI: 10.5281/zenodo.18216399
title: CEF_Bundle2_ComputationalArchitecture

description: ## **1. Purpose of This Bundle**

This bundle provides the **computational layer** of the Core Emotion Framework (CEF). It contains the formal ontologies, reasoning engine specifications, and knowledge graph architectures required to represent human emotional function in machine-readable formats.

While Bundle 1 provides the conceptual overview, Bundle 2 enables:

* **Semantic-Web Integration:** Using RDF/OWL and JSON-LD standards.* **Automated Reasoning:** Applying lawful emotional transitions and modulation via formal logic.* **Knowledge Graph (KG) Operations:** Structural rules for storing and querying emotional data.* **Validation:** Ensuring that any computational implementation remains "identity-preserving" and "contamination-free" according to the CEF canon.

---

## **2. Contents of This Bundle**

### **Core Specifications**

* **CEF_TS18.pdf:** Computational Ontology (The foundation of the machine-readable CEF).* **CEF_TS19.pdf:** Reasoning Engine Architecture (Logic for inference and state transitions).* **CEF_TS20.pdf:** Knowledge Graph Architecture (The semantic integration layer).* **CEF_TS21.pdf:** Population & Integration Specification (The data pipeline lifecycle).

### **Technical Appendices**

* **TS-18 (Ontology) Appendices:*** `CEF_Appendix_A`: JSON-LD Schema Specification.* `CEF_Appendix_B`: RDF/OWL Class Definitions.* `CEF_Appendix_C`: Knowledge Graph Node/Edge List.* `CEF_Appendix_D`: Validation Rules (TS-2 Integration).* `CEF_Appendix_E`: Validated Example Instances.

* **TS-19 (Reasoning) Appendices:*** `CEF_TS19_Appendix_B`: Reasoning Engine Pseudocode.* `CEF_TS19_Appendix_C`: Example Inference Walkthroughs.

* **TS-20 (Graph) Appendices:*** `CEF_TS20_Appendix_A`: Graph Serialization Formats.* `CEF_TS20_Appendix_B`: Query Language Specification (CEF-QL).* `CEF_TS20_Appendix_C`: Graph Validation Rules.

* **TS-21 (Pipeline) Appendices:*** `CEF_TS21_Appendix_A`: Population Pipeline Pseudocode.* `CEF_TS21_Appendix_B`: Integration Examples.

 

---

## **3. How to Cite This Bundle**

**Recommended citation:**Bulgaria, J. (2026). *Core Emotion Framework (CEF): Computational Architecture Bundle (Version 1.0).* OptimizeYourCapabilities.com. CC‑BY 4.0. 10.5281/zenodo.18216399

---

## **4. Relationships & Dependencies**

* **Continues:** Bundle 1 (Canon Overview) — Provides the high-level map for these technical specs.* **Prerequisite for:** Bundle 3 (EL-1 Lexicon) — The lexicon requires the TS-18 ontology for mapping.* **Governed by:** TS-1 through TS-17 (Conceptual Layer) — No computational process in this bundle may override the conceptual laws of the framework.

---

## **5. Usage Note**

This bundle is intended for developers, data scientists, and AI researchers. The included pseudocode and schemas are designed to be implementation-agnostic, allowing for deployment in Neo4j, Apache Jena, or custom graph-based reasoning systems.
DOI: 10.5281/zenodo.18216398
title: CEF_Bundle2_ComputationalArchitecture

description: ## **1. Purpose of This Bundle**

This bundle provides the **computational layer** of the Core Emotion Framework (CEF). It contains the formal ontologies, reasoning engine specifications, and knowledge graph architectures required to represent human emotional function in machine-readable formats.

While Bundle 1 provides the conceptual overview, Bundle 2 enables:

* **Semantic-Web Integration:** Using RDF/OWL and JSON-LD standards.* **Automated Reasoning:** Applying lawful emotional transitions and modulation via formal logic.* **Knowledge Graph (KG) Operations:** Structural rules for storing and querying emotional data.* **Validation:** Ensuring that any computational implementation remains "identity-preserving" and "contamination-free" according to the CEF canon.

---

## **2. Contents of This Bundle**

### **Core Specifications**

* **CEF_TS18.pdf:** Computational Ontology (The foundation of the machine-readable CEF).* **CEF_TS19.pdf:** Reasoning Engine Architecture (Logic for inference and state transitions).* **CEF_TS20.pdf:** Knowledge Graph Architecture (The semantic integration layer).* **CEF_TS21.pdf:** Population & Integration Specification (The data pipeline lifecycle).

### **Technical Appendices**

* **TS-18 (Ontology) Appendices:*** `CEF_Appendix_A`: JSON-LD Schema Specification.* `CEF_Appendix_B`: RDF/OWL Class Definitions.* `CEF_Appendix_C`: Knowledge Graph Node/Edge List.* `CEF_Appendix_D`: Validation Rules (TS-2 Integration).* `CEF_Appendix_E`: Validated Example Instances.

* **TS-19 (Reasoning) Appendices:*** `CEF_TS19_Appendix_B`: Reasoning Engine Pseudocode.* `CEF_TS19_Appendix_C`: Example Inference Walkthroughs.

* **TS-20 (Graph) Appendices:*** `CEF_TS20_Appendix_A`: Graph Serialization Formats.* `CEF_TS20_Appendix_B`: Query Language Specification (CEF-QL).* `CEF_TS20_Appendix_C`: Graph Validation Rules.

* **TS-21 (Pipeline) Appendices:*** `CEF_TS21_Appendix_A`: Population Pipeline Pseudocode.* `CEF_TS21_Appendix_B`: Integration Examples.

 

---

## **3. How to Cite This Bundle**

**Recommended citation:**Bulgaria, J. (2026). *Core Emotion Framework (CEF): Computational Architecture Bundle (Version 1.0).* OptimizeYourCapabilities.com. CC‑BY 4.0. 10.5281/zenodo.18216399

---

## **4. Relationships & Dependencies**

* **Continues:** Bundle 1 (Canon Overview) — Provides the high-level map for these technical specs.* **Prerequisite for:** Bundle 3 (EL-1 Lexicon) — The lexicon requires the TS-18 ontology for mapping.* **Governed by:** TS-1 through TS-17 (Conceptual Layer) — No computational process in this bundle may override the conceptual laws of the framework.

---

## **5. Usage Note**

This bundle is intended for developers, data scientists, and AI researchers. The included pseudocode and schemas are designed to be implementation-agnostic, allowing for deployment in Neo4j, Apache Jena, or custom graph-based reasoning systems.
DOI: 10.5281/zenodo.18217112
title: Arthropod Chemosynthesis: Sovereign Inversion of Nuclear Exclusion Zones via Periplaneta americana

description: Nuclear exclusion zones represent civilizational dead-ends—costly, politically paralyzed, and technologically stagnant. We invert the paradigm: contamination as feedstock, not waste. Using the Sovereign Constraint Mapper, we transform radiation toxicity from cleanup liability into economic input for cockroach (Periplaneta americana) bioremediation. Colonies ingest contaminated substrate, concentrate metals/radionuclides in exoskeletons via gut microbiome chelation, and enable continuous harvest of rare earth elements and medical isotopes. The system replaces cleanup costs with material revenue, demonstrating constraint-first environmental design. A screen recording of the live constraint inversion is included.

PATTERN RIGHTS ASSERTION

This work is licensed under CC BY 4.0 for text. Sovereign pattern rights are retained on the arthropod chemosynthesis methodology, constraint inversion protocol, and bioremediation system design. Defense applications subject to DFARS 252.227-7013 Limited Rights.
DOI: 10.5281/zenodo.18217111
title: Arthropod Chemosynthesis: Sovereign Inversion of Nuclear Exclusion Zones via Periplaneta americana

description: Nuclear exclusion zones represent civilizational dead-ends—costly, politically paralyzed, and technologically stagnant. We invert the paradigm: contamination as feedstock, not waste. Using the Sovereign Constraint Mapper, we transform radiation toxicity from cleanup liability into economic input for cockroach (Periplaneta americana) bioremediation. Colonies ingest contaminated substrate, concentrate metals/radionuclides in exoskeletons via gut microbiome chelation, and enable continuous harvest of rare earth elements and medical isotopes. The system replaces cleanup costs with material revenue, demonstrating constraint-first environmental design. A screen recording of the live constraint inversion is included.

PATTERN RIGHTS ASSERTION

This work is licensed under CC BY 4.0 for text. Sovereign pattern rights are retained on the arthropod chemosynthesis methodology, constraint inversion protocol, and bioremediation system design. Defense applications subject to DFARS 252.227-7013 Limited Rights.
DOI: 10.5281/zenodo.18217053
title: Genomic Dataset of 250 Metagenome-Assembled Genomes (MAGs) from a Wetland Microcosm Experiment

description: This dataset comprises a curated collection of 250 Metagenome-Assembled Genomes (MAGs) derived from wetland sediment microcosms treated for organochlorine bioremediation. It is structured to support the validation and re-analysis of microbiome studies focusing on pollutant degradation and greenhouse gas mitigation.

The dataset  includes four core components:







MAG Sequences (*.fna files): 250 high-quality draft genomes in FASTA format.




MAG Quality Control Table (quality_report.tsv):



Provides essential metrics for genome quality assessment.





MAG Taxonomic Annotations (gtdbtk.ar53.summary.tsv、gtdbtk.bac120.summary.tsv):



Contains the standardized taxonomic classification for each MAG.





MAG Abundance Profiles (bin_abun.tsv):





A matrix with MAGs as rows and experimental samples as columns. Values represent RPKM.




Enables the analysis of microbial population dynamics across different experimental conditions.






This integrated dataset serves as a foundational resource for:







Reproducing taxonomic profiling and differential abundance analyses.




Comparative genomic studies of wetland microbiomes.




Future investigations into microbial consortia for bioremediation and methanogenesis control.
DOI: 10.5281/zenodo.18217052
title: Genomic Dataset of 250 Metagenome-Assembled Genomes (MAGs) from a Wetland Microcosm Experiment

description: This dataset comprises a curated collection of 250 Metagenome-Assembled Genomes (MAGs) derived from wetland sediment microcosms treated for organochlorine bioremediation. It is structured to support the validation and re-analysis of microbiome studies focusing on pollutant degradation and greenhouse gas mitigation.

The dataset  includes four core components:







MAG Sequences (*.fna files): 250 high-quality draft genomes in FASTA format.




MAG Quality Control Table (quality_report.tsv):



Provides essential metrics for genome quality assessment.





MAG Taxonomic Annotations (gtdbtk.ar53.summary.tsv、gtdbtk.bac120.summary.tsv):



Contains the standardized taxonomic classification for each MAG.





MAG Abundance Profiles (bin_abun.tsv):





A matrix with MAGs as rows and experimental samples as columns. Values represent RPKM.




Enables the analysis of microbial population dynamics across different experimental conditions.






This integrated dataset serves as a foundational resource for:







Reproducing taxonomic profiling and differential abundance analyses.




Comparative genomic studies of wetland microbiomes.




Future investigations into microbial consortia for bioremediation and methanogenesis control.