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Preprint ARTICLE | doi:10.20944/preprints202406.0094.v1

Risk Management and Assessment Hybrid Framework for Business Process Reengineering Projects: Application in Auto-Motive Sector

RAFFAK Hicham, LAKHOUILI Abdallah, MANSOURI Mohamed

Subject: Engineering, Automotive Engineering Keywords: BPR; DEA; RDEA; Machine Learning; FMEA; PFMEA; Risk Prioritization; ANN

Online: 3 June 2024 (13:48:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1600.v1

In Vitro Antiviral Activity of Silydianin-Rich Extract from Silybum marianum Seeds Against Four Strains of Enteroviruses: EV71, Coxsackievirus B2, Coxsackievirus A10, and Poliovirus SL-1 and Its Impact on Improving Delayed Gastric Emptying in Mice

Houda Zaher, Sanae Lemrabet, Neri Koutchala, Bencharki Bouchaib

Subject: Medicine And Pharmacology, Complementary And Alternative Medicine Keywords: Gastroparesis; Enteroviral infections; Silydianin; Silybum marianum; Antiviral Activity; Gastrointestinal transit

Online: 22 August 2024 (08:25:24 CEST)

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Background/Objectives Gastroparesis, a chronic digestive disorder characterized by delayed gastric emptying, often results from diabetes, post-surgical complications, autoimmune diseases, and neurological disorders. In approximately 50% of cases, the cause is idiopathic gastroparesis (IGD). Recent studies suggest a link between chronic enteroviral infections and persistent gas-trointestinal symptoms, including delayed gastric emptying. This study investigates the effects of a silydianin-rich extract from Silybum marianum seeds on enteroviral infections in vitro and the mitigation of delayed gastric emptying in mice. Silydianin, a key bioactive compound known for its liver-protective and antioxidant properties, has not been extensively studied for its impact on enteroviral infections and gastroparesis; Methods NMR spectroscopy (¹H, ¹³C, and DEPT) identi-fied silydianin as the primary compound, with minor flavonolignans and trace amounts of an oxidation product. The study assessed the cytotoxicity and antiviral activity of the extract at various stages of the viral life cycle, including virucidal activity, cell protection, and post-infection effects, using neutral red assays in RD cells, with results confirmed by real-time PCR. The viruses studied included Coxsackievirus B2, Coxsackievirus A10, Poliovirus SL-1, and Enterovirus EV71. The impact on delayed gastric emptying was evaluated in a mouse model of gastroparesis using doses of 100 and 200 mg/kg compared to a control; Results: The silydianin-rich extract exhibited con-sistent antiviral activity, with the highest selectivity index (SI) for EV71 (4.08) during virucidal activity. It provided moderate cell protection, with EC50 values ranging from 120.88 to 186.10 µg/mL and SI values from 2.20 to 3.39. Post-infection treatment showed varying efficacy, with Coxsackie A10 demonstrating the highest SI (3.90). In vivo, the extract at 200 mg/kg significantly improved gastric emptying to 96.47% and slightly increased gastrointestinal transit from 50.33% to 61.46%; Conclusions These results suggest that silydianin may be effective in treating enteroviral infections and enhancing intestinal function, making it a promising candidate for gastroparesis treatment and warranting further research.

Preprint ARTICLE | doi:10.20944/preprints201608.0185.v1

Dispersion Operators Algebra and Linear Canonical Transformations

Raoelina Andriambololona, Ravo Tokiniaina Raymond Ranaivoson, Hasimbola Damo Emile Randriamisy, Hanitriarivo Rakotoson

Subject: Physical Sciences, Quantum Science And Technology Keywords: Dispersion operator; Lie algebra; Linear Canonical Transformation; Quantum theory; Phase space representation

Online: 20 August 2016 (10:55:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0342.v1

1,2-Dicinnamoyl-Sn-Glycero-3-Phosphocholine Enhances Insulin Sensitivity and Increases the Expression Level of mtDNA-Encoded Genes in Insulin-Resistant 3T3-L1 Adipocytes – a Preliminary Study

Aneta Cierzniak, Anna Gliszczyńska, Małgorzata Małodobra-Mazur

Subject: Medicine And Pharmacology, Medicine And Pharmacology Keywords: insulin resistance; cinnamic acid; phospholipid derivative; phenolic acid; 1,2-di-CA-PC

Online: 5 August 2024 (13:46:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0476.v1

Metabolomics on Apple (Malus domestica) Cuticle—Search for Authenticity Markers

Kamila Bechynska, Jiri Sedlak, Leos Uttl, Vit Kosek, Petra Vackova, Vladimir Kocourek, Jana Hajslova

Subject: Chemistry And Materials Science, Food Chemistry Keywords: Malus domestica; apple cuticle; UHPLC-HRMS/MS; metabolomic fingerprints; classification models; markers; wax esters

Online: 8 April 2024 (03:04:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1752.v1

DATIV – Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi Based Distributed Sensors

Gazi Hasanuzzaman, Tom Buchwald, Christoph Schunk, Christoph Egbers, Andreas Schröder, Uwe Hampel

Subject: Engineering, Control And Systems Engineering Keywords: particulate matter; COVID-19; distributed sensors; Raspberry Pi; WiFi; open source; low cost measurement system; indoor ventilation

Online: 26 April 2024 (12:36:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202406.0678.v1

Optimization Of The Search For Neuroprotectors Among Bioflavonoids

Igor Belenichev, Victor Ryzhenko, Olena Popazova, Nina Bukhtiyarova, Nadia Gorchakova, Valentyn Oksenych, Oleksandr Kamyshnyi

Subject: Medicine And Pharmacology, Medicine And Pharmacology Keywords: informational technologies; multiple sclerosis; virtual screening; bioflavonoids; neuroprotection

Online: 11 June 2024 (11:07:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0023.v1

Co-occurrence of Borrelia burgdorferi sensu lato and Babesia spp. DNA in Ixodes ricinus Ticks Collected from Vegetation and Pets in the City of Poznań, Poland

Justyna Liberska, Jerzy Michalik, Julia Olechnowicz, Miroslawa Dabert

Subject: Biology And Life Sciences, Parasitology Keywords: Ixodes ricinus; Borrelia burgdorferi s.l.; Babesia microti; Babesia venatorum; Babesia canis; Borrelia miyamotoi; coinfections, babesiosis, urban green areas

Online: 1 March 2024 (05:42:09 CET)

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Green spaces localized in cities create favourable environmental conditions for Ixodes ricinus, the most widespread and important vector of tick-borne pathogens in Central Europe. In this study, we described the prevalence of Borrelia burgdorferi s.l. and Babesia species found in mono- and double infections among I. ricinus ticks occurring in urban areas of the city of Poznań, west-central Poland. Two tick groups were examined: (i) a group of 1,029 host-seeking ticks (460 nymphs, 289 females, and 280 males and (ii) a group of 1,268 engorged female ticks removed from 1,115 tick-infested animals, dogs and cats. The overall prevalence of B. burgdorferi s.l. found in host-seeking ticks was almost two-fold higher in comparison to ticks derived from pets (8.7 vs. 4.7%, respectively, χ2 test, P = 0.001). Borrelia afzelii and B. garinii were the most prevalent species both in ticks from vegetation (3.7% and 3.7%, respectively) and from pets (3.7% and 0.6%, respectively). Babesia infections were slightly more common in feeding ticks compared to those from vegetation (6.0 vs. 4.7%, respectively), however, the difference was not significant. Three Babesia species including Ba. microti, Ba. venatorum and Ba. canis were identified. Babesia canis and Ba. microti were the most prevalent in host-seeking (2.6% and 1.4%, respectively) and feeding ticks (2.8% and 2.2%, respectively), whereas Ba. venatorum was the rarest piroplasm. All Ba microti obtained sequences (n=42) were identical to Ba. microti genotype "Jena/Germany" that is considered as pathogenic to humans. Furthermore, the sequences of Ba. venatorum (n=17) were identical with those isolated from patients in Italy, Austria and Poland. Altogether, out of 121 Babesia-positive ticks, 19.8% were simultaneously infected with B. burgdorferi s.l. spirochetes. We found similar prevalences of co-infections in host-seeking (1.1%) as well as in feeding ticks (1.0%). In the first group, Ba. canis prevailed in coinfections (73%), mostly with B. afzelii and B. garinii, in the second group, Babesia microti dominated with B. afzelii (92.7%). This is the first finding documenting the co-occurrence of both pathogens in ticks from companion animals. The detection of Ba. microti and Ba. venatorum sequences identical to strains pathogenic to humans as well as predominance of LB spirochetes, B. afzelii and B. garinii in I. ricinus from vegetation and animals indicates that there is a potential risk of acquiring human babesiosis and/or Lyme borreliosis in urban areas of the city of Poznań. Although, the overall risk of encountering a Ba. microti and B. burgdorferi s.l. co-infected tick was low (1.0%), the potential for more severe clinical symptoms and complications deserves notice. A relatively high infection rates of Ba. canis in dog-derived ticks (3.2%) and in host-seeking ticks (2.6%), suggests that I. ricinus could potentially be involved in the circulation of this piroplasm in areas, where the competent vector, Dermacentor reticulatus is absent or rare.

Preprint ARTICLE | doi:10.20944/preprints202407.1467.v1

Localized Crop Classification by NDVI Time Series Analysis of Remote Sensing Satellite Data; Applications for Mechanization Strategy and Integrated Resources Management

Hafiz Md-Tahir, Hafiz Sultan Mahmood, Muzammil Husain, Ayesha Khalil, Muhammad Shoaib, Mahmood Ali, Muhammad Mohsin Ali, Muhammad Tasawar, Yasir Ali Khan, Usman Khalid Awan, Muhammad Jehanzeb Masud Cheema

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Remote sensing; Geographical information system; Vegetation index; LULC classification; Agricultural mechanization; Strategic planning; Resources management; Artificial intelligence algorithms; Crop phenology, Satellite data; Precision agriculture

Online: 18 July 2024 (11:28:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0349.v1

Spatial-Temporal Variations of Human Impact on Forest Ecological Functions in the Yellow River Basin from 2004 to 2018

Xiaodi Zhao, Qingjun Wu, Guangyu Wang, Ram P. Sharma, Linyan Feng, Lang Bai

Subject: Social Sciences, Geography, Planning And Development Keywords: Forest ecological function; human activities; spatial-temporal variation; geographic temporal weighted regression

Online: 4 April 2024 (05:34:17 CEST)

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Human activities (e.g., exploitation, utilization, and conservation) exert substantial impact on forest ecological functions (FEF). The human influence on FEF significantly varies across developmental stages, which are attributed to the temporal and spatial in nature. This study evaluates some notable FEF indices (FEFI) in the 448 counties within the Yellow River basin (YRB) using panel data from the Seventh to Ninth National Forest Inventory. Data analysis involves employing the residual trends, geographical and temporal weighted regression. Results indicate that, firstly, the overall forest ecological function in the YRB is moderate to inferior, with superior FEF in counties endowed with more natural forest resources. Afforestation demonstrates a short-term improvement, but its effectiveness diminishes over time. Secondly, the positive spatial correlation is stronger among counties, characterized by both high-high and low-low agglomeration effects. Scattered planting, simple stand structure, and concentrated harvesting of forests at the identical stand ages hinder the formation of complex and large-scale FEF agglomerations. Thirdly, significant spatial-temporal differences exist in the impact of human activities on FEF. In the upper reaches of the basin, increased vegetation coverage through agricultural and forestry production benefited FEF, however, some over-exploitation of forests and grasslands is observed there. In the middle reaches, the economic development, expanding population and the greening activities help to improve FEF effectively, but excessive water using in agricultural production brought more difficulties to FEF improvement. In the lower reaches of the basin, improved wastelands and forest protection positively influence FEF. This study recommends that county governments should prioritize forest management with multi-species and multi-layered complex forests. Each county should define its position in regional development and ecological protection, considering the potential impacts on neighboring regions. This holistic approach promotes more effective integrated regional management.

Preprint ARTICLE | doi:10.20944/preprints202407.0657.v1

Impact of Alcalase Hydrolysis and Simulated Gastrointestinal Digestion on the Release of Bioactive Peptides From Erythrina edulis (Chachafruto) Proteins

Jessica L. Correa, Jose Edgar Zapata, Blanca Hernández-Ledesma

Subject: Biology And Life Sciences, Food Science And Technology Keywords: Erythrina edulis; enzymatic hydrolysis; in vitro gastrointestinal digestion; peptides; antioxidant; macrophages.

Online: 9 July 2024 (14:03:19 CEST)

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Preprint REVIEW | doi:10.20944/preprints202407.1623.v1

Artificial Intelligence Techniques in Grapevine Research: A Comparative Study with Extensive Review on Datasets, Diseases, and Techniques Evaluation

Paraskevi Gatou, Xanthi Tsiara, Alexandros Spitalas, Spyros Sioutas, Gerasimos Vonitsanos

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; machine learning; grapevine; diseases; vineyards; smart sensors; smart agriculture

Online: 19 July 2024 (13:38:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0576.v1

Reactivity and Heavy Metal Adsorption Behaviour of Graphene Oxide Nanoparticle From First Principle Investigations: Case of Pb and CD

Preslie S. Nianga-Obambi, Dick Hartmann Douma, Anne Justine Etindele, Abdulrafiu Tunde Raji, Brice rodrigue Malonda-Boungou, Bernard M'PASSI-MABIALA, Stephane Kenmoe

Subject: Chemistry And Materials Science, Theoretical Chemistry Keywords: Graphene oxide; Density Functional Theory; Heavy metals; Adsorption

Online: 9 May 2024 (09:15:26 CEST)

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Graphene oxide (GO) is considered as one of the promising adsorbents for the removal of various heavy metal contaminants in aquatic environment, due to its beneficial structural, chemical and electronic properties. Using the density functional theory (DFT) approach, we investigate the reactivity of a model GO nanoparticule (C30H14O15) toward neutral and charged lead (Pb) and cadmium (Cd) atoms. We found the model metal-free GO to have a high chemical reactivity. To study the adsorption of the metal atoms on the GO nanoparticle, we have used a single and doubly-adsorbed neutral (Pb0 and Cd0) and charged (Pb2+, Cd2+) atoms. After identified possible adsorption sites on the GO, we found that a single charged metal ion binds more strongly than a neutral atom of the same type. To determine the possibility of multiple adsorptions of GO nanoparticle, two metal atoms of the same species are co-adsorbed on its surface. Our calculations reveals a site-dependent adsorption energy such that when two atoms of the same specie are adsorbed at sites Si and Sj , the binding energy per atom depends on the whether one of the two atoms is adsorbed firstly on the Si or Sj sites. It is also found that the binding energy per atom for two co-adsorbed atoms of the same specie is less than the binding energy of a singly-adsorbed atom which suggests that atoms may become less likely to be adsorbed on the GO nanoparticle when their concentrations increase. This applies to both neutral and charged atoms. We adduce the origin of this observation to be interplay between metal-metal interaction on the one hand and GO-metal on the other, with the former resulting in a less binding for the charged adsorbed metals in particular, due to repulsive interaction between two positively charged ions. The frontier molecular orbitals analysis and the calculated global reactivity descriptors of the respective GO- metal complexes revealed that all the GO-metal complexes have a smaller HOMO-LUMO gap (HLG) relative to that of pristine metal-free GO nanoparticle. This suggests that although the GO-metal complexes are stable, they are less stable compared to metal-free GO nanoparticles. The negative values of the chemical potentials obtained for all the GO-metal complexes further confirms their stability. Our work calculates parameters that will be crucial to rational design of GO nanoparticles for Pb abd Cd ions contaminants removal, and may find application in water purification for example.

Preprint ARTICLE | doi:10.20944/preprints202407.2462.v1

A Multi-Scale Mask Convolution based Blind Spot Network for Hyperspectral Anomaly Detection

Zhiwei Yang, Rui Zhao, Xiangchao Meng, Gang Yang, Weiwei Sun, Shenfu Zhang, Jinghui Li

Subject: Computer Science And Mathematics, Geometry And Topology Keywords: hyperspectral anomaly detection; multi-scale anomaly targets; blind spot network; multi-scale mask convolution

Online: 30 July 2024 (11:39:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1858.v1

A Dynamic Simulation of a Piezoelectric Energy Harvesting System Integrated with a Closed-Loop Voltage Source Converter for Sustainable Power Generation

Ahmed K Ali, Ali Abdulwahhab Abdulrazzaq, Ali H. Mohsin

Subject: Engineering, Electrical And Electronic Engineering Keywords: controlled PWM rectifier; P&; O MPPT; closed-loop converter; piezoelectric energy harvesting; sustainable renewable energy

Online: 26 August 2024 (17:08:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1395.v1

Application of Machine Learning Techniques to Classify Twitter Sentiments Using Vectorization Techniques

Manjog Padhy, Umar Muhammad Modibbo, Rasmita Rautray, Subhranshu Sekhar Tripathy, Sujit Bebortta

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Sentiment Classification; Twitter Sentiment Analysis; Word Count Vectorization; Machine Learning

Online: 20 August 2024 (09:24:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202406.0577.v1

Factors Associated With Complications of Snakebite Envenomation in Health Facilities in the Cascades Region of Burkina Faso, 2016 to 2021

Réné Kinda, Sidikiba Sidibe, Dramane Zongo, Tieba Millogo, Alexandre Delamou, Seni Kouanda

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: Snakebite; Envenomation; Complications

Online: 11 June 2024 (08:48:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201611.0116.v1

Evaluation of Diversification Techniques for Legal Information Retrieval

Marios Koniaris, Ioannis Anagnostopoulos, Yannis Vassiliou

Subject: Computer Science And Mathematics, Information Systems Keywords: diversity; algorithms; legal information retrieval

Online: 23 November 2016 (09:50:24 CET)

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Preprint ARTICLE | doi:10.20944/preprints202404.0182.v1

Hybrid Genetic Algorithm and Tabu Search for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants

Khaled Alhamad, Yousif Alkhezi

Subject: Computer Science And Mathematics, Discrete Mathematics And Combinatorics Keywords: preventive maintenance; scheduling; optimization; genetic algorithm; tabu search; metaheuristic

Online: 2 April 2024 (12:56:52 CEST)

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Preprint REVIEW | doi:10.20944/preprints202404.0112.v1

Chalcones – Features, Identification Techniques, Attributes and Application in Agriculture

Magdalena Dziągwa-Becker, Marta Oleszek, Sylwia Zielińska, Wiesław Oleszek

Subject: Environmental And Earth Sciences, Environmental Science Keywords: chalcones; biopesticides; herbicides; insecticides; low risk active substances

Online: 1 April 2024 (14:59:18 CEST)

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Preprint REVIEW | doi:10.20944/preprints202408.0062.v1

A Survey of Quantitative Techniques in Electricity Consumption – A Global Perspective

Atif Maqbool Khan, Artur Wyrwa

Subject: Business, Economics And Management, Econometrics And Statistics Keywords: Survey; Quantitative Methods; Energy Consumption

Online: 1 August 2024 (11:55:20 CEST)

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Preprint REVIEW | doi:10.20944/preprints202409.1068.v1

Various Prospects of Biodiesel Production: Techniques and Challenges

Muhammad Ammad Jamil, Shamsa Aziz, Muhammad Salman Khalid

Subject: Social Sciences, Transportation Keywords: Biodiesel; Biodiesel production; Transesterification; Non-edible feedstock; Catalysts; Properties

Online: 14 September 2024 (10:16:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202010.0366.v1

Operational Optimization at Signalized Metering Roundabouts Using Cuckoo Search/Local Search Algorithm

Hong Ki An, Yao Liu, Dong Sun Kim

Subject: Engineering, Automotive Engineering Keywords: Metering roundabout; Detector location; AIMSUN; Cucksoo search/Local search algorithm

Online: 19 October 2020 (10:41:42 CEST)

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Preprint REVIEW | doi:10.20944/preprints202406.1495.v1

Understanding Aerosol-Cloud Interactions Through Lidar Techniques: A Review

Francesco Cairo, Luca Di Liberto, Davide Dionisi, Marcel Snels

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Aerosol; Cloud; Lidar

Online: 21 June 2024 (10:03:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1320.v1

Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques

Osama A. Salman, Gábor Hosszú

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Feature Selection; Hyperparameters; Machine Learning; Phylogenetics; Scriptinformatics; Consistency Index (CI); False Rejection Rate (FRR); False Acceptance Rate (FAR); Classification

Online: 20 August 2024 (10:42:40 CEST)

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Preprint REVIEW | doi:10.20944/preprints202409.0715.v1

Detrimental Effects of Abiotic Stress on Wheat and Its Management Techniques

Mohammad Nur Alam, Md. Zaherul Islam, Murad Ahmed Farukh, Zhulong Chan, Mst. Masuma Akhter, Md. Tanvir Abedin, Md. Monoar Hossain

Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: Drought; Heat; Genes; Antioxidants; Salinity; Oxidative stress

Online: 10 September 2024 (12:54:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1160.v1

Impact Assessment of Photovoltaic Panels with Life Cycle Analysis Techniques

Nikolaos Skarkos, Anthoula Menti, Konstantinos Kalkanis, Ioannis Chronis, Constantinos S. Psomopoulos

Subject: Environmental And Earth Sciences, Sustainable Science And Technology Keywords: Photovoltaic (PV) technologies; Photovoltaic (PV) panels; Life cycle analysis (LCA); Life cycle impact assessment (LCIA)

Online: 20 February 2024 (14:04:20 CET)

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Preprint REVIEW | doi:10.20944/preprints202403.1401.v1

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs

Jill Meynen, Peter Adriaensens, Maarten Criel, Evelyne Louis, Karolien Vanhove, Michiel Thomeer, Liesbet Mesotten, Elien Derveaux

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: biomarkers; lung cancer; metabolomics; NMR (nuclear magnetic resonance)

Online: 25 March 2024 (07:06:46 CET)

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Preprint REVIEW | doi:10.20944/preprints202405.1987.v1

Experimental Techniques for Testing the Properties of Construction Materials

Ahed Habib, Ausamah AL Houri, Salah Al-Toubat, M. Talha Junaid

Subject: Engineering, Civil Engineering Keywords: Construction materials characterization; Microstructure testing; Structural behavior analysis; Sustainability in construction

Online: 30 May 2024 (07:40:10 CEST)

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The field of construction materials is pivotal in developing sustainable and resilient infrastructure. This demands continuous research to understand the properties and behaviors of these materials under diverse conditions. Although advancements in material science and numerical modeling have been significant, experimental testing remains indispensable for a thorough comprehension of material characteristics, particularly under extreme stresses and environmental factors. This need has forced the development of a wide array of testing techniques, each designed to evaluate specific engineering properties, thus creating a complex and varied landscape of experimental methodologies. This study provides a comprehensive overview of both conventional and innovative experimental testing techniques used to characterize construction materials. It explores the related methodologies and identifies potential gaps in their application within the industry. The spectrum of testing covered includes mechanical, chemical, thermal, microstructural, durability, physical, rheological properties, and non-destructive testing methods. Mechanical tests assess strength, hardness, and fatigue, whereas chemical analyses utilize techniques such as spectroscopy and chromatography. Thermal properties are examined using thermogravimetric analysis, and microstructural characteristics are explored through advanced imaging techniques. Durability testing focuses on materials’ resistance to environmental challenges, while physical properties tests evaluate aspects like porosity and water absorption. Rheological and non-destructive tests further examine materials’ behavior and integrity without causing damage. By discussing these methodologies, the study sheds light on various approaches to material evaluation and aims to enhance the selection, application, and development of testing standards. This overview seeks to inform and inspire future research and innovation in the science of construction materials, contributing to the development of more resilient and sustainable construction practices.

Preprint ARTICLE | doi:10.20944/preprints202405.1856.v1

Effects of Reduced N Application, Nitrification Inhibitor, and Straw Incorporation on Fertilizer-N Fates in Maize Cropping System: A Field ¹⁵N Tracer Study in Northeastern China

Zhi Quan, Shanlong Li, Zhifeng Xun, Chang Liu, Dong Liu, Yanzhi Wang, Xinghan Zhao, Ming Yang, Caiyan Lu, Xin Chen, Yunting Fang

Subject: Environmental And Earth Sciences, Soil Science Keywords: ; soil N turnover; straw application; nitrification inhibitor; ¹⁵N labeling; ¹⁵N recovery; ¹⁵N retention; nitrogen use efficiency; Mollisol ;

Online: 29 May 2024 (04:15:24 CEST)

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Reducing fertilizer-N rate, applying nitrification inhibitor (NI), and incorporating straw are widely recommended to improve N use efficiency of crops and decrease N losses. However, how these practices affect crop N uptake by regulating the fertilizer-N fate during the growing season is not well understood. We conducted a field 15N tracer study to explore the effectiveness of reduced N application, NI, and straw incorporation on fertilizer-N fates for maize cultivation in Northeast China. The following six treatments were used: 1) no N fertilization (control); 2) 200 kg urea-N ha−1 (100%N); 3) 200 kg urea-N ha−1 and 2400 kg dry-straw ha−1 (100%N+S); 4) 160 kg urea-N ha−1 (80%N, i.e., 20% reduction of N fertilization); 5) 160 kg urea-N ha−1 and nitrification inhibitor (Nitrapyrin) (80%N+NI); 6) 160 kg urea-N ha−1, nitrification inhibitor and 2400 kg dry-straw ha−1 (80%N+NI+S). Our results showed that the five N fertilization treatments yielded 16%–25% more grain and 39%–60% more crop N uptake than the control receiving no N fertilizer, but the differences among the five treatments were not statistically significant. In contrast to plant growth, changes in fertilizer-N fates in soil and plant pools were more pronounced. Compared with the 100%N treatment, 20% fertilizer-N reduction (80%N) decreased 15N concentration in topsoil and plant pools but increased the proportion of plant 15N recovery at harvesting (N use efficiency, NUE15N, 60% vs. 50%) (P < 0.05). Nitrapyrin co-application (80%N+NI) delayed soil nitrification and increased soil 15N retention at harvesting (52% vs. 36%), thereby decreasing NUE15N significantly (P < 0.05). Straw incorporation (100%N+S) decreased fertilizer-N retention compared with NI co-application because it promoted NUE15N significantly (P < 0.05). The combined application of NI and straw (80%N+NI+S) was more conducive to fertilizer-N retention in soil. Our findings demonstrate that NI and straw additions are efficient strategies for stabilizing fertilizer-N in soils and potentially minimizing N loss; however, their effects on NUE15N vary and the related mechanism must be further clarified in long-term trials.

Preprint ARTICLE | doi:10.20944/preprints202408.1777.v1

Influence of Harvesting Stage on the Phytochemical Composition, Antioxidant, and Antidiabetic Activity of Immature Ceratonia siliqua L. Pulp from Béni-Mellal-Khenifra Region, Morocco: In Silico, In Vitro, and In Vivo Approaches

Salah Laaraj, Hanane Choubbane, Aziz Tikent, Amal Elrherabi, Ayoub Farihi, Meriem Laaroussi, Mohamed Bouhrim, Abdelaaty A. Shahat, Younes Noutfia, Rashed N. Herqash, Fatiha Chigr, Souad Salmaoui, Kaoutar Elfazazi

Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: immature carob pulp; phytochemical compounds; antioxidant activity; in silico; in vitro and in vivo studies; antidiabetic agent

Online: 26 August 2024 (16:51:23 CEST)

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Ceratonia siliqua L. is a medicinal plant that has long been used in traditional Moroccan medicine to treat many diseases. This study aimed to assess the impact of the stages of the immature phase of carob pulp (M1, M2, M3, M4, and M5) on phytochemical composition, antioxidant activity, and antidiabetic activity of Ceratonia siliqua L. The identification of the phenolic profile by HPLC-UV/MS-MS and the study of the antidiabetic effect by in silico, in vitro, and in vivo studies were carried out for extracts with a high content of phenolic compounds from immature wild carob pulp from the communes of Timoulit (TM), Bin Elouidane (AW), and Ouaouizerth (TG) in the province of Azilal in the Beni Mellal-Khenifra region. The results revealed a gradual increase in total sugar content over the pulp's ripening period, reaching a value of 2134 ±56.23 mg GE/100 g fresh matter (FM) for TG. The three locations showed peak values for total polyphenol content (TPC), total flavonoid content (TFC), and total condensed tannin (TCT) at the M2 stage. AW has the highest concentrations of TPC (3819 ± 226.4 mg GAE/100 g FM), TFC (1034 ± 57.08 mg QE/100 g FM), and TCT (1472 ± 28.46 mg CE/100 g FM). The DPPH assay (7892 ± 296.1 mg TE/100 g FM) and the FRAP assay (278.2 ± 7.85 mg TE/100 g FM) both demonstrate that the TG zone is a highly potent antioxidant zone. In contrast, the AW site exhibits a markedly elevated value of 725.4 ± 103.6 mg TE/100 g FM in the ABTS assay. HPLC-UV-MS/MS analysis showed that the methanolic extracts of immature carob pulp (MEICP) from the three areas contained several different chemical compounds. The most prevalent were 3-O-p-coumaroyl-5-O-caffeoylquinic acid, quercetin 3-methyl ether, gallic acid, and galloylquinic acid. Immature carob pulp extract. (ICPE) from AW showed the strongest in vitro inhibition of pancreatic α-amylase (IC50 = 0.405 µg/mL) and TG extracts were most potent against intestinal α-glucosidase (IC50 = 0.063 µg/mL). In vivo, AW, TG, and TM extracts significantly reduced postprandial glycemia in rats, with AW having the greatest effect. These results highlight the antidiabetic potential of ICPE. The 3-O-p-Coumaroyl-5-O-caffeoylquinic acid showed a better affinity for α-amylase compared to acarbose and interacted significantly with several amino acid residues of the enzyme. Similarly, this molecule and 3,4-Dicaffeoylquinic acid demonstrated a strong affinity for α-glucosidase, suggesting their potential as natural inhibitors of enzymes involved in carbohydrate metabolism. Most of the compounds are not substrates of P-glycoprotein and exhibit high intestinal absorption. Furthermore, the majority of these compounds do not act as inhibitors or substrates of CYP450 enzymes, reinforcing their suitability for development as oral medications. These results underscore the potential of immature carob pulp as a promising antidiabetic agent.

Preprint OPINION | doi:10.20944/preprints201608.0016.v1

Dark Side of Molecular Techniques: How to Fix It ?

Vikash Bhardwaj

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: parallel DNA; antiparallel DNA; PCR; CRISPR; nucleic acid hybridization; microarray; siRNA

Online: 2 August 2016 (10:42:27 CEST)

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Preprint REVIEW | doi:10.20944/preprints202405.1212.v1

Important Repercussions of the COVID-19 Pandemic Lifestyle Avoided by Researchers? Face Masks and Temporomandibular Disorders: A Systematic Search and Review

Szymon Jozef Pietrzyk, Emilia Kielczynska, Martyna Kowalczyk, Mateusz Mazurek, Zygmunt Antoni Domagala

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: temporomandibular joint disorder; TMD; SARS-CoV-2 outbreak; COVID-19; COVID-19 pandemic; face masks; prolonged face mask use; TMJ; complications

Online: 20 May 2024 (12:37:23 CEST)

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Preprint REVIEW | doi:10.20944/preprints202404.1947.v1

Understanding Aβ Peptide Binding to Lipid Membranes. A Biophysical Perspective

HASNA AHYAYAUCH, Massimo Masserini, Alicia Alonso, Félix M. Goñi

Subject: Biology And Life Sciences, Biophysics Keywords: Aβ42; β-amyloid; Aβ membrane binding; ganglioside; sphingomyelin; cholesterol; isothermal calorimetry; Langmuir balance; Alzheimer’s disease

Online: 30 April 2024 (14:34:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0803.v1

Cascading Landslide: Kinematic and Fem Analysis through Re-2 Mote Sensing Techniques

Nicola Sciarra, Mirko Francioni, Massimo Mangifesta, Diego Di Martire, Domenico Calcaterra, Luigi Guerriero

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Cascading landslides; Slope stability; InSAR interferometry; Pixel Offset; Finite element 31 Analysis; Numerical Modelling

Online: 12 August 2024 (11:37:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0012.v1

Flexible Techniques to Detect Typical Hidden Errors in Large Longitudinal Datasets

Renato Bruni, Cinzia Daraio, Simone Di Leo

Subject: Computer Science And Mathematics, Computer Science Keywords: big data; information processing; information reconstruction; data quality: longitudinal data sequences

Online: 1 March 2024 (10:33:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints202409.1215.v1

A Survey System for Artificial Intelligence-Based Painting Using Generative Adversarial Network Techniques

Ming-Der Jean, Chaoyang Zhang, Xiang Li

Subject: Social Sciences, Cognitive Science Keywords: AI painting software; generative adversarial networks; fuzzy hierarchical analysis; evaluation models

Online: 16 September 2024 (11:39:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1636.v1

A 2-Year Randomized Clinical Trial of Three Bonding Techniques in Non-carious Cervical Lesions

Eftychia Pappa, Grigoria Gkavela, Ioanna Sampri, Konstantinos Masouras, Christos Rahiotis, Afrodite Kakaboura

Subject: Medicine And Pharmacology, Dentistry And Oral Surgery Keywords: self-etch; total-etch; selective enamel etching; retention; caries; marginal adaptation; marginal staining; non-caries cervical lesions

Online: 24 April 2024 (17:54:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1280.v1

Effects of Three Yeast Strains on In Vitro Rumen Fermentation of Corn Stover and a Total Mixed Ration

Bexy Gonzalez-Mora, Francisco Castillo-Rangel, Joel Dominguez-Viveros, Perla Lucia Ordoñez-Baquera, Michael E. Hume, Robin C. Anderson, Monserrath Félix-Portillo, Agustin Corral-Luna, Jaime Salinas-Chavira, Yamicela Castillo-Castillo, Oscar Ruiz-Barrera

Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: microbial feed additives; probiotic; Candida norvegensis; Pichia guilliermondii; Saccharomyces cerevisiae

Online: 19 August 2024 (05:49:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202409.0663.v1

Adaptive Hyperactivity and Clinical and Laboratory Biomarker Search: The Case of Old Elders in the Blue Zone of Sardinia

Alessandra Scano, Germano Orrù, Goce Kalcev, Giulia Cossu, Massimo Tusconi, Maura Spada, Laura Atzori, Caterina Ferreli, Flavio Cabitza, Diego Primavera, Federica Sancassiani

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: Bipolar Disorders; BD; Laboratory Medicine; Applied Biomedical Technologies; Bipolar Spectrum; Prevention; New Technologies; Hyperactive; Blue Zone; Biomarker

Online: 9 September 2024 (11:25:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.2295.v1

Application of Experimental Configurations of Seismic and Electric Tomographic Techniques to the Investigation of Complex Geological Structures

Vasileios Gkosios, John D. Alexopoulos, Konstantinos Soukis, Ioannis-Konstantinos Giannopoulos, Spyridon Dilalos, Dimitrios Michelioudakis, Nicholas Voulgaris, Thomas Sphicopoulos

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: ERT; SRT; seismic sources comparison; spectral analysis; forward modelling; GPR; magmatic intrusion

Online: 29 July 2024 (11:01:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1216.v1

Integration of Isotopic and Nuclear Techniques to Assess Water and Soil Resources Degradation. A Critical Review

José L. Peralta Vital, Lucas E. Calvo Gobbetti, Yanna Llerena Padrón, Francisco Heriberto Martínez Luzardo, Oscar Díaz Rizo, Reinaldo Gil Castillo

Subject: Environmental And Earth Sciences, Water Science And Technology Keywords: Fallout radionuclide (FRN); Fingerprint (FP); Isotope Hydrology (IH); Soil degradation; Water resources degradation; Integrated nuclear techniques

Online: 19 August 2024 (17:53:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1181.v1

Evaluation of Different Soil Salinity Indices Using Remote Sensing Techniques in Siwa Oasis, Egypt

Omnia H Salem, Zhonghua Jia

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Soil Salinity; Remote sensing; Landsat; Spectral Indices; Correlation; Land cover; Siwa; Egypt

Online: 21 February 2024 (11:38:31 CET)

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Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

Preprint ARTICLE | doi:10.20944/preprints202405.2135.v1

Evaluating of Noise Reduction Techniques for Turboengine Test Stands: A Preliminary Analysis

Laurentiu Cristea, Marius Deaconu

Subject: Engineering, Aerospace Engineering Keywords: baffle attenuator; turboengine stand; experimental validation; Embleton's method; anechoic chamber; rectangular duct flow.

Online: 31 May 2024 (10:56:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0535.v1

Individual Piglet Detection in Weaning Stage using Deep Learning Techniques

Erika Fernanda Lozano Cruz, Ilda de Fátima Ferreira Tinôco, Robinson Osorio Hernández, Jairo Alexander Osorio Saraz, Rodrigo Cupertino Bernardes, Verónica González Cadavid, Ana Paola Montoya Ríos, Rafaella Resende Andrade, Gianluca Bambi

Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: Object detection; Yolov7; VGG Image Annotator; pigs’ individual detection; swine individual detection

Online: 9 May 2024 (14:21:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1884.v1

Investigating Effective Factors in Solving Partial Differential Equations using Deep Learning Techniques

Parastoo Kabi-Nejad

Subject: Computer Science And Mathematics, Mathematics Keywords: Partial Differential Equations; Machine learning; Neural Networks; Computational Modeling; Feature Identification

Online: 29 April 2024 (10:25:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0358.v1

Iterative Qubits Management for Quantum Search

Wenrui Mu

Subject: Computer Science And Mathematics, Information Systems Keywords: Quantum Search; Qubit Management; Iterative Search

Online: 23 September 2022 (05:25:28 CEST)

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Preprint REVIEW | doi:10.20944/preprints202405.1772.v1

A Comparative Analysis of Retrofitting Techniques for Seismically Vulnerable Historical Building

John Philip M. Rivera

Subject: Engineering, Civil Engineering Keywords: Retrofitting; Seismic Resilience; Historical Buildings; Base Isolation; Strengthening of Masonry; Steel Bracing Systems; FRP Wrapping; Damping Devices

Online: 27 May 2024 (22:23:21 CEST)

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This study presents a comprehensive comparative analysis of retrofitting techniques aimed at enhancing the seismic resilience of seismically vulnerable historical buildings. Recognizing the dual objectives of structural safety and architectural preservation, this research evaluates and compares several advanced retrofitting methods, including base isolation, strengthening of masonry, steel bracing systems, Fiber-Reinforced Polymer (FRP) wrapping, and damping devices. Each technique is critically assessed based on its effectiveness in mitigating seismic risks, its compatibility with historical architectural features, and its applicability to various building types. Base isolation is highlighted for its ability to decouple buildings from ground motion, thereby significantly reducing seismic forces and protecting architectural integrity. Strengthening of masonry through the use of fiber-reinforced polymers and steel elements enhances the ductility and strength of masonry walls, making them more resilient to seismic forces. Steel bracing systems are shown to provide essential lateral support, particularly in timber-framed structures, improving overall stability and reducing deformation during earthquakes. FRP wrapping is identified as a versatile technique that strengthens structural elements without compromising aesthetic value, making it suitable for reinforcing concrete and masonry components. Damping devices, including viscous dampers and tuned mass dampers, are discussed for their ability to dissipate seismic energy and control structural vibrations, offering a minimally invasive solution that preserves historical aesthetics. The study also addresses several challenges and research gaps associated with these retrofitting techniques, such as ensuring architectural compatibility, assessing long-term material performance, optimizing cost-effectiveness, and navigating complex regulatory frameworks. By advancing knowledge in these areas, the research aims to foster interdisciplinary collaboration and innovation in the development of retrofitting solutions. Ultimately, this study contributes to the ongoing efforts to safeguard historical buildings against seismic hazards. By leveraging cutting-edge technologies and best practices in structural engineering and architectural conservation, stakeholders can develop sustainable, cost-effective, and culturally sensitive retrofitting strategies that protect valuable cultural heritage for future generations.

Preprint ARTICLE | doi:10.20944/preprints202406.0118.v1

Tool-Emitted Sound Signal Decomposition Using Wavelet and Empirical Mode Decomposition Techniques—A Comparison

Emerson Raja Joseph, Hossen J, Bhuvaneswari Thangavel, Azlina Nor, Thong Leng Lim, Pushpa Rani Mariathangam

Subject: Engineering, Electrical And Electronic Engineering Keywords: empirical mode decomposition; Hilbert Huang transform; wavelet decomposition; discrete wavelet transform; turning process

Online: 4 June 2024 (08:19:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1566.v2

Weather Forecasting Using Machine Learning Techniques: Rainfall and Temperature Analysis

Adil Hussain, Ayesha Aslam, Sajib Tripura, VIneet Dhanawat, Varun Shinde

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: rainfall prediction, temperature prediction, ensemble classifier, rain prediction, weather prediction

Online: 13 September 2024 (11:43:09 CEST)

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Preprint REVIEW | doi:10.20944/preprints202407.1451.v1

Rethinking Public Participation in Forest Policies: A Literature Review of Participatory Techniques

Isabella De Meo, Alessandro Paletto, Sofia Baldessari

Subject: Environmental And Earth Sciences, Environmental Science Keywords: participatory democracy; citizen involvement; decision making; inclusiveness; degree of in-volvement

Online: 17 July 2024 (14:01:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0998.v1

Investigation of CFRP Concrete Reinforcement Ageing Using Microwave Infrared Thermography Method (MIRT)

Barbara Szymanik, Sam Ang Keo, Franck Brachelet, Didier Defer

Subject: Engineering, Civil Engineering Keywords: Microwave thermography; carbon-fiber-reinforced polymer (CFRP); defect; ageing; modeling with COMSOL

Online: 16 April 2024 (07:36:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0987.v1

Does Athletes' Respiratory Muscle Strength Affect Max VO2 Kinetics?

Gökhan Deliceoğlu, Veli O. Çakır, Banu Kabak, Halil Ibrahim Ceylan, Raul Ioan Muntean, Valentina Ștefănică

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: Respiratory; maximal inspiratory pressure; expiratory pressure; MaxVO2; athletes

Online: 18 March 2024 (09:39:18 CET)

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Preprint REVIEW | doi:10.20944/preprints201611.0138.v1

Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques

P. Kalavathi, K. Senthamilselvi, V. B. Surya Prasath

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: computational imaging; midsagittal plane; inter-hemispheric fissure; symmetry analysis; neuroimaging

Online: 28 November 2016 (02:03:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202409.0823.v1

The Impact of Breast Cancer Risk Factors: Socio-Economic, Hormonal, and Clinical Insights from Hassan II Regional Oncology Center, Morocco

Mouas Fatima Ezahra, Doudach Latifa, Addoum Boutaina, Attaleb Mohammed, Mohammed El Mzibri, Benbacer Laïla, Rais Ghizlane, Fechtali Taoufiq

Subject: Medicine And Pharmacology, Other Keywords: Breast cancer; socio-economic; factors; hormonal; clinical; treatments; stategies

Online: 11 September 2024 (00:14:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0389.v1

Toward Enhanced Seed Potato Yield: Exploring Ultrasonication Techniques in Agricultural Engineering

Piotr Pszczółkowski, Barbaś Piotr, Alaa K. Farhan, Barbara Krochmal-Marczak, Barbara Sawicka

Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: Cultivation technology; Agricultural engineering; Piezoelectric transducers; Genetic traits; Environmental conditions; Climate adaptation; Ultrasonication; Seed potato

Online: 5 April 2024 (08:23:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0937.v1

Challenges and Opportunities in One Health: Google Trends Search Data

Lauren Wisnieski, Karen Gruszynski, Vina Faulkner, Barbara Shock

Subject: Public Health And Healthcare, Public, Environmental And Occupational Health Keywords: Google Trends; disease prediction; Lyme disease; Lyme; Big Data; One Health; negative binomial; mixed models; zoonotic disease; tick-borne disease

Online: 11 August 2023 (11:01:40 CEST)

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Preprint ESSAY | doi:10.20944/preprints202012.0156.v1

Evidence-Based Management of Gout - A Systematic Search and Review

Md Abu Bakar Siddiq

Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: gout; hyperuricemia; lesinurad; life style; prednisolone; uric acid; urate oxidase

Online: 7 December 2020 (13:10:24 CET)

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Gout is the most common form of inflammatory arthritis. Hyperuricaemia is the pre-requisite for gout and is influenced by variable modifiable and non-modifiable risk factors. Clinical features unique for gout are due to deposition of monosodium urate (MSU) crystal in articular and extra articular tissues. Among various treating agents, anti-inflammatory drugs and urate lowering therapies (ULT) are used widely and successfully, however, non-medicinal means are also effective in the disorder. In their updated guidelines, ACR (2012) and EULAR (2016) recommended both medicinal and non-medicinal approaches that could be used in treating gout, though some of the recommendations are based on lower level of evidence. Moreover, researchers’ continued effort in finding new gout managing agents appear promising, for example, role of Lesinurad in gout management (CLEAR1, CLEAR2). In this new synthesis the author is aimed to provide updated information on gout management based on a systematic review including published work within last ten years between 2008 and 2018 and for this purpose, using ‘clinical trials in gout management’ string, published worked searched in PubMed database from 1st September 2018 to 30 October 2018. Besides the recent ACR and EULAR evidence based management guidelines, the author reviewed another 91 (total 93) articles to make this new draft – 39 articles describe role of pharmacological agents and 54 describe different gout risks, pharmacokinetics/pharmacodynamics of ULT, association between raised sUA level and renal impairment, efficacy of non-pharmacological agents in reducing sUA. According to published work, anti-inflammatory agent is the most appropriate drug group in mitigating inflammatory symptoms of gout, though they often adversely affect over other vital 2 organs with impaired function. Besides ULT, uricase analogues are also found useful in non refractory gout. Since anti-inflammatory agents and ULT contraindicate in some clinical conditions, intra-articular steroid and or adrenocorticotropic hormone (ACTH) are appropriate alternatives instead. However, head-to-head comparison between different NSAIDs, NSAID and prednisolone, NSAID and colchicine are yet to perform. Use of combined anti-inflammatory preparations in gout is also based on lower level of evidence. Regarding effective maximum dose and long-standing impact of ULT on vital organs we are yet to reach a conclusion. Likewise, non-medicinal approaches are widely using in achieving target sUA level, though some of them are based on biased study outcomes and or study with inadequate power, requiring further analysis. Among non-pharmacological approaches, life-style modification, restriction of purine rich diets, avoidance of gout inciting agents are important, but inconclusive. Educating patients’ about diseases, risk factors, available treatment options and side effects from them are also important in terms of achieving sUA level, nevertheless too much counseling sometimes could be worthless.

Preprint ARTICLE | doi:10.20944/preprints202406.1948.v1

Machine Learning Meets Meta-heuristics: Bald Eagle Search Optimization and Red Deer Optimization for Feature Selection in Type II Diabetes Diagnosis

Harikumar Rajaguru, Dinesh Chellappan

Subject: Engineering, Bioengineering Keywords: Classifiers; Bald Eagle Search Optimization; Red Deer Optimization; Diabetic Detection; Performance Analysis; Feature extraction.

Online: 27 June 2024 (13:53:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202401.0056.v1

Optimization of Greedy Randomized Adaptive Search Procedure

Ahmed Tlili, Salim Chikhi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Mental representation; GRASP metaheuristic; optimization

Online: 2 January 2024 (09:34:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202108.0018.v1

Proximal Policy Optimization for Radiation Source Search

Philippe Proctor, Christof Teuscher, Adam Hecht, Marek Osiński

Subject: Physical Sciences, Radiation And Radiography Keywords: deep reinforcement learning; source search and localization; active search; gamma radiation; source parameter estimation; sequential decision making; non-convex environment}

Online: 2 August 2021 (11:14:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201608.0184.v1

Search for dynamical origin of social networks

Michail Zak

Subject: Computer Science And Mathematics, Computer Science Keywords: instability; attractors; randomness; quantum-classical hybrid

Online: 20 August 2016 (05:39:37 CEST)

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Preprint REVIEW | doi:10.20944/preprints202407.2283.v1

State of the Art Synthesis of Ag-ZnO-Based Nanomaterials by Novel Atmospheric Pressure Microplasma Techniques

Ayesha Khalid, M. Naeem, Omar Atrooz, M. R. Mozafari, Fatemeh Anari, Elham Taghavi, Umair Rashid, Bushra Aziz

Subject: Medicine And Pharmacology, Other Keywords: Atmospheric microplasma technique; core shall nanoparticles; antibacterial activity; antifungal activity; silver nanoparticles

Online: 29 July 2024 (09:59:25 CEST)

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Preprint REVIEW | doi:10.20944/preprints202405.1350.v1

Smear Classification of Cardiopulmonary Resuscitation Techniques and Devices

Muhammad Feras Iftikhar, Linta Iftikhar, Shahzad Hassan, Muhammad Iftikhar Hanif

Subject: Medicine And Pharmacology, Cardiac And Cardiovascular Systems Keywords: ; cardiopulmonary resuscitation; techniques and devices classification; chest compression ;

Online: 21 May 2024 (07:09:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201607.0051.v1

Search for QPOs in the Light Curve of the Blazar OJ287: Preliminary Results from 2015/16 Observing Campaign

S. Zola, M. Valtonen, G. Bhatta, A. Goyal, B. Debski, A. Baran, J. Krzesinski, M. Siwak, S. Ciprini, A. Gopakumar, H. Jermak, K. Nilsson, D. Reichart, K. Matsumoto, K. Sadakane, K. Gazeas, M. Kidger, V. Piirola, F. Alicavus, K.S. Baliyan, A. Berdyugin, D. Boyd, M. Campas Torrent, F. Campos, J. Carrillo Gomez, D.B. Caton, V. Chavushyan, J. Dalessio, D. Dimitrov, M. Drozdz, A. Erdem, A. Escartin Perez, V. Fallah Ramazani, A.V. Filippenko, F. Garcia, F. Gomez Pinilla, M. Gopinathan, J.B. Haislip, J. Harmanen, G. Hurst, K.M. Ivarsen, M. Jelinek, A. Joshi, M. Kagitani, N. Kaur, N. Karaman, W.C. Keel, A.P. LaCluyze, B.C. Lee, E. Lindfors, J. Lozano De Haro, J.P. Moore, R. Naves Nogues, A.W. Neely, R.H. Nelson, W. Ogloza, S. Okano, J.C. Pandey, M. Perri, P. Pihajoki, G. Poyner, J. Provencal, T. Pursimo, A. Raj, R. Reinthal, S. Sadegi, T. Sakanoi, J.-L. Salto Gonzales, T. Schweyer, F.C. Soldan Alfaro, E. Sonbas, I. Steele, J.T. Stocke, J. Strobl, L.O. Takalo, T. Tomov, L. Tremosa Espasa, J.R. Valdes, J. Valero Perez, F. Verrecchia, J.R. Webb, M. Yoneda, M. Zejmo, W. Zheng, J. Telting, J. Saario, T. Reynolds, A. Kvammen, E. Gafton, R. Karjalainen, P. Blay

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: galaxies: active; BL Lacertae objects: individual (OJ 287); super massive black holes

Online: 18 July 2016 (10:46:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1698.v2

Efficient Solutions for Large-Scale Max-Cut Problems: A Hybrid Local Search Heuristic Approach and Comparative Analysis with Quantum Annealing

Haibo Wang, Bahram Alidaee, Lutfu Sagbansua

Subject: Business, Economics And Management, Other Keywords: hybrid heuristics; quantum annealing solver; max-cut

Online: 25 June 2024 (00:23:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0213.v2

The Impact of SMOTE and ADASYN on Random Forest and Advanced Gradient Boosting Techniques in Telecom Customer Churn Prediction

Mehdi Imani, Zahra Ghaderpour, Majid Joudaki, Ali Beikmohammadi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: customer churn prediction; machine learning; classification techniques; SMOTE; ADASYN; Random Forest; XGBoost; LightGBM; CatBoost

Online: 10 April 2024 (07:57:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0157.v1

In Search of Easily Accessible and Reliable Malignancy Biomarkers in Liquid Biopsies: The Case of miRNAs in Extracellular Vesicles in the Plasma of Patients with Papillary Thyroid Cancer

Giuseppa D'Amico, Radha Santonocito, Godfrey Grech, Giuseppa Graceffa, Calogero Cipolla, Federics Scalia, Samuele Raccosta, Mauro Manno, Everly Conway de Macario, Alberto J. L. Macario, Francesco Cappello, Francesca Rappa, Celeste Caruso Bavisotto, Claudia Campanella

Subject: Biology And Life Sciences, Life Sciences Keywords: thyroid cancer; extracellular vesicles; microRNAs; cancer biomarkers; chaperone system; Hsp60; CCT; liquid biopsy

Online: 2 August 2024 (12:21:28 CEST)

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Preprint REVIEW | doi:10.20944/preprints202409.0443.v1

Metabolomics and Lipidomics Techniques, Databases and Software Used for Studying Gastrointestinal Parasites of Animals

Phurpa Wangchuk, Karma Yeshi

Subject: Biology And Life Sciences, Parasitology Keywords: Gastrointestinal parasites; Small molecules; Database; Metabolomics; Lipidomics; Artificial intelligence

Online: 5 September 2024 (09:27:13 CEST)

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Preprint REVIEW | doi:10.20944/preprints202103.0523.v1

'Copper and Bronze in Art' and the Search for Rare Corrosion Products

Gerhard Eggert

Subject: Chemistry And Materials Science, Metals, Alloys And Metallurgy Keywords: basic copper(II) formate; ‘Black Spots’; chalconatronite; copper(II) hydroxide; copper sulfide; curly malachite; namuwite; sodium copper(II) formate; verdigris

Online: 22 March 2021 (11:50:06 CET)

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Preprint ARTICLE | doi:10.20944/preprints202405.1504.v1

Enhancing Corporate Security: A Microservices Approach to Monitoring with Spyware Techniques and Prediction Models

Anubis Graciela de Moraes Rossetto, Darlan Noetzold, Luis Augusto Silva, Valderi Reis Quietinho Leithardt

Subject: Computer Science And Mathematics, Security Systems Keywords: electronic monitoring; hate speech; data leakage; prediction; microservices

Online: 23 May 2024 (07:53:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1365.v1

Deep Learning in Finance: A Survey of Applications and Techniques

Ebikella Mienye, Nobert Jere, George Obaido, Ibomoiye Domor Mienye, Kehinde Aruleba

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: CNN; Deep Learning; Finance; GRU; LSTM; Machine learning; RNN

Online: 20 August 2024 (03:42:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201608.0202.v2

Remote Sensing and Data Mining Techniques for Assessing the Urban Fabric Vulnerability to Heat Waves and UHI

Flavio Borfecchia, Vittorio Rosato, Emanuela Caiaffa, Maurizio Pollino, Luigi De Cecco, Luigi La Porta, Simone Ombuen, Lorenzo Barbieri, Federica Benelli, Flavio Camerata, Valeria Pellegrini, Andrea Filpa

Subject: Environmental And Earth Sciences, Environmental Science Keywords: HR satellite remote sensing; urban fabric vulnerability; UHI & heat waves; landsat & MODIS sensors; LST & urban heating; segmentation & objects classification; data mining; feature extraction & selection; stepwise regression & model calibration

Online: 26 October 2021 (13:11:23 CEST)

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Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

Preprint ARTICLE | doi:10.20944/preprints202405.1538.v1

A Possibilistic Formulation of Autonomous Search for Targets

Zhijin Chen, Branko Ristic, Du Yong Kim

Subject: Computer Science And Mathematics, Signal Processing Keywords: Possibility theory; autonomous systems; robust estimation

Online: 23 May 2024 (11:16:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0896.v1

Interpolation Once Binary Search over a Sorted List

Jun-Lin Lin

Subject: Computer Science And Mathematics, Computer Science Keywords: binary search; interpolation search; interpolated binary search

Online: 15 April 2024 (08:44:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0253.v1

Theoretical Search for Gravitational Bound States of Tachyons

Charles Schwartz

Subject: Physical Sciences, Space Science Keywords: General Relativity; Schwarzschild metric; circular flows; tachyons; neutrinos; Dark Matter; black holes

Online: 15 August 2022 (08:26:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202111.0107.v1

Dealing with the Ambiguity of Glycan Substructure Search

Vincenzo Daponte, Catherine Hayes, Julien Mariethoz, Frederique Lisacek

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: Glycan structure; Knowledge representation; Pattern recognition; Ontology; Semantic web

Online: 5 November 2021 (08:34:05 CET)

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Preprint ARTICLE | doi:10.20944/preprints202107.0241.v1

Consumer Behaviour in Search of a Circular Economy

Antoni Seguí-Alcaraz

Subject: Business, Economics And Management, Accounting And Taxation Keywords: circular economy; environment; consumer

Online: 12 July 2021 (11:14:35 CEST)

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Preprint REVIEW | doi:10.20944/preprints202402.0357.v1

A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)

Rajvardhan Patil, And Venkat Gudivada

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: language models; PLMs; largel anguage model; LLMs; natural language processing; NLP; literature review; survey; review

Online: 6 February 2024 (13:37:47 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0410.v1

Treated Wastewater Assessment to Optimize Agricultural Water Reuse in Al-Qatif Region Saudi Arabia Using Hybrid Machine Learning Techniques

Syed Muzzamil Hussain Shah, Mohamed A. Yassin, Sani I. Abba, Dahiru U. Lawal, Farouq Aliyu, Ebrahim Hamid Hussain Al-Qadami, Zahiraniza Mustaffa, Chaitanya B. Pande, Saad Sh. Sammen, Isam H. Aljundi

Subject: Environmental And Earth Sciences, Water Science And Technology Keywords: electrical conductivity; treated waste water; machine learning; prediction analysis; agricultural irrigation; water security; SDG-6

Online: 7 March 2024 (07:53:10 CET)

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In the era of mounting water scarcity, particularly in arid regions, the agricultural sector is striving to optimize the water resource management practices. Treated wastewater (TWW) has emerged as a viable alternative to freshwater for irrigation, offering a sustainable solution to water conservation. However, ensuring the safety and quality of TWW is paramount to safeguard for both crop health and environmental integrity. Electrical conductivity (EC), a critical factor in assessing TWW suitability for irrigation, can significantly impact crop yields and soil health since it is directly linked to the concentration of dissolved salts and ions. Therefore, this study delves into the development of advanced predictive models for EC assessment by employing supervised machine learning (ML) techniques like the Support Vector Regression (SVR), Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR). The TWW samples collected from Al-Qatif area, Saudi Arabia were assessed in the lab through a sensor-based real-time monitoring system integrated with Internet of Things (IoT) network and a multiprobe device. The key water quality parameters assessed involved, temperature (T), pH, Oxidation Reduction Potential (ORP), Resistivity (RES), Total Dissolved Solids (TDS), Salinity and Turbidity which served as the foundation for these models, given their profound influence on and their anticipated impact on EC levels. Following feature selection, two distinct model combinations were identified for the SVR, ANFIS and MLR models. Furthermore, to evaluate prediction performance, four statistical criteria, including coefficient of determination (R²), correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE), were employed. Overall, the comparative performance results proved that ANFIS-M2 indicated the strongest predictive capability with the R² value of 0.99572 and 0.75145 and the RMSE values of 0.00965 and 0.01134, respectively in both calibration and verification stages.

Preprint ARTICLE | doi:10.20944/preprints202402.1756.v1

Malian children core gut mycobiome

Abdourahim Abdillah, Kodio Aly, Stéphane Ranque

Subject: Biology And Life Sciences, Immunology And Microbiology Keywords: Fungal gut community structure; gut mycobiome; core mycobiome; ITS metabarcoding; children; Dogon country

Online: 29 February 2024 (17:02:42 CET)

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Preprint ARTICLE | doi:10.20944/preprints202404.1716.v1

Laser Forced Dehydration of Benign Vascular Lesions of the Oral Cavity: A Valid Alternative to Surgical Techniques

Margherita Gobbo, Luca Guarda-Nardini

Subject: Medicine And Pharmacology, Dentistry And Oral Surgery Keywords: Vascular Malformation; Diode Laser; Angioma; Blue light; Conservative

Online: 26 April 2024 (11:00:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0698.v1

A Comparative Study of Susceptibility and Hazard for Mass Movements Applying Quantitative Machine Learning Techniques. Case Study: Northern Lima Commonwealth, Peru

Edwin Noe Badillo-Rivera, Manuel Daniel Olcese Huerta, Ramiro Santiago Chirinos, Teófilo Ivan Poma Inche, Neftalí Euclides Muñoz Fernandez, Carlos Alberto Rojas-León, Teodosio Juan Chávez Campos, Luz de Fátima Eyzaguirre Gorvenia, César Augusto Rodriguez Aburto, Fernando José Oyanguren Ramírez

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: mass movement, weight evidence, principal component analysis, machine learning.

Online: 10 May 2024 (14:15:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1125.v1

Water Quality of Eastern Mediterranean Catchments Subject to Different Environmental Pressures Employing Autonomous Unmanned Surface Vehicles (USVs)

Georgios Katsouras, Elias Dimitriou, Sotirios Karavoltsos, Stylianos Samios, Aikaterini Sakellari, Angeliki Mentzafou, Nikolaos Tsalas, Michael Scoullos

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: remote sensing; water quality; autonomous USV; inland and coastal waters; telemetric stations

Online: 20 February 2024 (11:49:48 CET)

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Preprint REVIEW | doi:10.20944/preprints202407.0729.v1

Minimally Invasive Lumbar Disc Hernia Surgery: Mapping the Landscape of Techniques and Outcomes through Bibliometric Analysis of Current Meta-analyses

Halil Bulut, Kursat Guner, Omer Polat, Peter Derman

Subject: Medicine And Pharmacology, Orthopedics And Sports Medicine Keywords: Lumbar disc herniation; discectomy; full-endoscopic lumbar discectomy (FELD); automated percutaneous discectomy (AUTD); Microendoscopic Discectomy (MED)

Online: 9 July 2024 (12:18:32 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202409.0315.v1

Imaging Techniques for the Analysis of Blood-Brain Barrier and Gliovascular Unit Dysfunction

Samantha Golf, Carmen Munoz-Ballester, Benjamin Heithoff, Kijana George, Stefanie Robel

Subject: Biology And Life Sciences, Neuroscience And Neurology Keywords: Blood-Brain Barrier; BBB; Impairment; Tight Junctions; Astrocyte Endfeet; Endothelial Cells; Basement Membrane

Online: 4 September 2024 (08:33:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202311.0077.v1

Network Reconfiguration for Loss Reduction using Tabu Search and a Voltage Drop

Dionicio Zocimo Ñaupari Huatuco, Luiz Filho, Franklin Simeon Pucuhuayla, Yuri Percy M. Rodriguez

Subject: Engineering, Electrical And Electronic Engineering Keywords: network reconfiguration; distribution system; optimization; Tabu Search; minimization; distribution system loss; OpenDSS; Python

Online: 2 November 2023 (07:01:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202406.0667.v1

Relationship between Vitamin D Insufficiency, Lipid Profile and Atherogenic Indices in Healthy Women Aged 18–50 Years.

Ilham Lhilali, Noura Zouine, Lode Godderis, Adil El Midaoui, Samir El Jaafari, Younes Filali-Zegzouti

Subject: Medicine And Pharmacology, Clinical Medicine Keywords: Vitamin D; 25-OH vitamin D; Dyslipidemia; Atherogenic indices.

Online: 11 June 2024 (11:53:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.1196.v1

Power Consumption Modeling of Airconditioning Units in an Educational Building Using Polynomial and Neural Network Fitting Techniques

Stanley Glenn Brucal, Aaron Don Africa, Roy Francis Navea, Ana Antoniette Illahi, Aristotle Ubando, Marla Maniquiz-Redillas, Reggie Gustilo, Pocholo James Loresco

Subject: Engineering, Electrical And Electronic Engineering Keywords: power modeling; curve fitting; neural network fitting; regression analysis; power stabilization; thermal condition; indoor air quality

Online: 20 March 2024 (09:50:19 CET)

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Preprint ARTICLE | doi:10.20944/preprints202404.1912.v1

Assessing the Impact of Urban Expansion on the Urban Environment in Riyadh City (2000–2022) Using Geospatial Techniques

Shaykhah Mohammed Alajizah, Hamad Ahmed Altuwaijri

Subject: Environmental And Earth Sciences, Geography Keywords: urban expansion; urban environment; geospatial technologies; remote sensing; Thermal Environmental Index

Online: 29 April 2024 (10:12:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202406.0524.v1

Optimization of Lead-Free Sn-Based Perovskite Solar Cells using SCAPs-1D Simulation Techniques

Awais Maqsood, Muhammad Irfan Abid, Muhammad Kamran, Marek Turzyński, Mehdi Tlija, Ehab Ghith

Subject: Engineering, Electrical And Electronic Engineering Keywords: Perovskite solar cells; Lead-free; Tin-based; SCAPs-1D Simulation and Performance optimization

Online: 11 June 2024 (08:33:23 CEST)

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Preprint REVIEW | doi:10.20944/preprints202403.0225.v1

Port Scanning Techniques Tools and Detection

Sam Coyle

Subject: Computer Science And Mathematics, Security Systems Keywords: Port Scanning; TCP; TCP SYN; UDP; Stealth Scan; ZMap; NMap; MASSCAN; Anomaly based detection; Signature based detection

Online: 5 March 2024 (06:30:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202408.1487.v1

Cross-country Ski Skating Style Sub-techniques Detection and Skiing Characteristic Analysis on Snow Using High Precision GNSS

Shunya Uda, Naoto Miyamoto, Kiyoshi Hirose, Hiroshi Nakano, Thomas Stöggl, Vesa Linnamo, Stefan Lindinger, Masaki Takeda

Subject: Biology And Life Sciences, Other Keywords: High precision GNSS; Cross-country skiing; Skating techniques; Sub-technique classification

Online: 21 August 2024 (04:25:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0152.v1

Effects of Icon Grouping based on Familiartity on Search Times and Eye Movements

Yujeong Ha, Seung-Kweon Hong

Subject: Engineering, Industrial And Manufacturing Engineering Keywords: visual search; icon grouping; familiarity of icon; color contrast ratio

Online: 2 August 2024 (10:45:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0321.v1

Quality and Readability of Google Search Information on HoLEP for Benign Prostate Hyperplasia

Yam Ting Ho, Jeremy Saad, Femi E Ayeni, Mohan Arianayagam, Bertram Canagasingham, Ahmed Goolam, Nicola Jeffrey, Mohamed Khadra, Raymond Ko, Nicholas Mehan, Sachinka Ranasinghe, Celi Varol, Jonathan Kam, Isaac A Thangasamy

Subject: Medicine And Pharmacology, Urology And Nephrology Keywords: Urological surgical procedures; Prostatectomy; Transurethral resection of prostate; Prostatic hyperplasia; Consumer health information, Health literacy; Health education

Online: 6 March 2024 (04:50:41 CET)

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Preprint REVIEW | doi:10.20944/preprints202401.2087.v1

Understanding and Modeling the Pathophysiology of Hydrocephalus: In Search of Better Treatment Options

Verayna Newland, Bonnie L. Blazer-Yost

Subject: Biology And Life Sciences, Neuroscience And Neurology Keywords: choroid plexus; cerebrospinal fluid; electrolyte transport; ventriculomegaly; preclinical hydrocephalic models

Online: 31 January 2024 (01:51:21 CET)

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Preprint ARTICLE | doi:10.20944/preprints202305.1456.v1

Distraction and Visual Search Characteristics of Young Drivers When Using Navigation System Displays

Tamer Yared, Patrick Patterson, Ahmad Mumani

Subject: Engineering, Safety, Risk, Reliability And Quality Keywords: Navigation System display; Distraction; Visual Search Behavior; Fixation; Dwell; Eye-tracking; Young Drivers; Night Driving; Driving Safety

Online: 22 May 2023 (03:38:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0397.v1

Improve Ubiquitination-site Prediction Using Physicochemical Properties and Machine Learning with Grid Search

Xiaoye Mo, Samuel Cho, Xia Jiang

Subject: Computer Science And Mathematics, Computer Science Keywords: ubiquitination; ubiquitination-site; PCP; protein physicochemical properties; prediction; machine learning; grid search

Online: 29 June 2022 (07:48:46 CEST)

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ABSTRACT Background Ubiquitination plays an important role in protein post-translational processes and has been found to be involved in a number of regulatory functions including proteasome degradation, DNA repair, transcription, signal transduction, endocytosis, and sorting. As the identification of ubiquitination site is critical to furthering our understanding of the mechanism of ubiquitination, various experimental and machine learning methods have been used to conduct this task. It has been an important but challenging task to improve the accuracy of ubiquitination site prediction. In this research, we explore the possibility of improving the prediction performance of machine learning by incorporating grid search in the training process. Method We developed grid search procedures for each of six widely used machine learning methods including NB, LR, DT, SVM, LASSO, and KNN, and applied them to ubiquitination site prediction using the six PCP datasets that were previously developed. For each of the ML methods, we developed a set of values for each of the tunable hyperparameters available to the method. These sets of values then can be combined to form a large grid of hyperparameter settings, and each of these settings is used in the grid search. We integrated 5-fold cross-validation in grid search to train and test ML models and applied an additional independent validation procedure by conducting a pre-training 80-20 sample split. We evaluated the performance of the six methods by comparing them side by side for each of the six datasets. We also compared the grid search results with the results that were previously published without doing grid search. To optimize the prediction performance, we trained 1.1 million ML models in total through grid search. Results We compared the overall prediction performance of these six methods, as well as their prediction performance when working with balanced vs. imbalanced data, and large-scale vs. small-scale data. From the perspective of dataset, we find that the overall performance of every PCP dataset has been significantly improved in this study compared to the previous study, with the percentage increase of the average AUC of all six datasets ranging from 7.9% (PCP-4) up to 17.0% (PCP-1). From the perspective of method, we find that three out of four methods significantly benefit from grid search comparing to their previously published non-grid search results, with the maximum AUC improvement as high as 47% (LASSO on PCP-5), 43.3% (NB on PCP-1), and 33.7% (SVM on PCP-6). SVM overall ranks number one, followed by KNN as the number two performer based on their average AUCs on all datasets. But these two also ranked the top two (KNN 76 days and SVM 15 days) in terms of the total running time that they need to do grid search. We also find that SVM, KNN, and DT tend to handle small-scale and imbalanced datasets better, while LR, and LASSO are doing well with large-scale and balanced datasets. NB is more sensitive to data imbalance while less sensitive to the size of a dataset. Conclusions Our results show that using grid search has improved the performance of ubiquitination prediction significantly. We find that the performance of a method is closely related to its hyperparameter setting and the type of data it handles. Even though SVM is on average an outperformer, none of the methods can provide the best performance for all datasets. When sufficient computing resources are well accessible, grid search is an effective way to identify both a top performing model for a machine learning method and a suitable machine learning method for a particular dataset.

Preprint ARTICLE | doi:10.20944/preprints202405.1619.v1

Application of Aquifer Delineation and Hydrogeophysical Techniques in Estimating Groundwater Recharge to Enhance Water Allocation in Groundwater-Dependent Areas, Northern Cape, South Africa

Lucky Baloyi, Thokozani Kanyerere, Innocent Muchingami, Harrison Pienaar

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: apparent resistivity; electric potential difference; magneto-telluric; unconfined; confined

Online: 24 May 2024 (10:01:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202312.1168.v1

Search for Novel Phases in Y-Ba-Cu-O Family

Danijel Djurek

Subject: Physical Sciences, Condensed Matter Physics Keywords: thermo-acoustic resonator; delafossites; spin-charge separation; spinons; holons

Online: 19 December 2023 (04:46:17 CET)

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