bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Optimized Vibration-based Energy Harvester for Leak Detection in Wall-mounted Water Pipelines
Authors: Mysorewala Muhammad Faizan , Virk Mati-Ur-Rasool Ashraf , Syed Mujahid Naqeebuddin , Saif Abdul-Wahid , Cheded Lahouari , Shafiq Saifullah , Sattar Karim 
Published: September 2024

Abstract

In this paper, we propose a novel circuit with piezoelectric energy harvesters that we developed to power accelerometer sensor nodes placed at optimal locations to maximize energy harvesting, and timely and accurately detect leaks in the pipeline. To reduce energy consumption in sensing and computations, strategies such as duty cycling and a reduction in the number of samples have been incorporated. Due to the conflicting relationship between leak detection accuracy, delay in detecting the leak, and energy consumed by the sensor node, a novel optimization problem is formulated to address this trade-off by linking some crucial design parameters, namely the number of samples per cycle, node sleep time, delay in leak detection, required leak detection accuracy, and remaining sensor node energy. The resulting optimization problem is solved using graphical method. Experimental data is gathered for the harvested energy from a home-grown lab testbed consisting of a Wall-Mounted Pipeline (WMP) system, and various techniques are suggested to increase energy generation. Subsequently, the experimental data is utilized to solve the optimization problem by providing optimal node parameters for a selected remaining node energy after a certain specified number of sampling cycles, as well as a desired leak detection delay and accuracy. The results obtained corroborate our selection of the values of the various parameters used, and the theory underlying our novel optimization problem. The results obtained also provide ample encouragement to pursue different alternative solutions discussed in this paper, as part of our future work in this important practical area.
Optimizing Landslide Susceptibility Mapping in Oued Guebli Watershed: A Comparative Study of Deep Learning, Support Vector Machines, Logistic Regression with Spatial Validation and AUC- ROC Analysis
Authors: Mebirouk Nadjib , Amrane Moussa , Messast Salah 
Published: September 2024

Abstract

methods
Logistic Regression (LR), Support Vector Machines (SVM), and Deep Learning (DL) to identify areas most susceptible to landslides. The selection of causative factors was based on a detailed statistical study examining the relationship between landslide occurrence and specific characteristics such as slope, lithology, Normalized Difference Vegetation Index (NDVI), Topographic Wetness Index (TWI), land use, proximity to roads, watercourses, and geological faults. These factors were essential in generating accurate and reliable susceptibility maps using Geographic Information Systems (GIS) technology. Metrics of performance, including accuracy, precision, F1-score, specificity, sensitivity, and RMSE, were used to evaluate the performance of the models, which were verified, validated, and compared using the area under curve (AUC) value of the Receiver Operating Characteristics Curves (ROC) method and the spatial validation technique. This spatial validation evaluated the percentage of active landslide areas in the high and very high susceptibility classes. The DL and SVM models demonstrated a very high concentration of landslide points in these classes, with 99% and 98% respectively, whereas the LR model showed 89%. In terms of AUC validation, the DL model achieved the highest AUC value of 0.9894, followed by the SVM model followed with an AUC of 0.9873, while LR demonstrated a lower AUC of 0.9093. These precise and reliable results help to identify high-risk areas more effectively, thereby safeguarding residents and preserving infrastructure in the Oued Guebli watershed. The choice of the DL model as the most effective method underscores its capability to deliver accurate susceptibility maps, which are important for informed decision-making and risk management.
Computational Identification and Validation of Novel Inhibitors Targeting LLM Genes in Staphylococcus aureus for Antimicrobial Drug Development
Authors: Fakuade Ayodeji Adebayo , oyeniyi Peace Victoria , Adetunji Iyanuoluwa Hannah , Ojo Oluwadamilola Victoria , Clement John Dilma , Ishaya Bulus Joseph 
Published: September 2024

Abstract

Staphylococcus aureus is a formidable pathogen responsible for a wide variety of illnesses, including some that are resistant to several antibiotics. Targeting the key llm genes in S. aureus, which are crucial for bacterial lysis and methicillin resistance, is an attractive method for accelerating the development of novel antimicrobial drugs. The aim of this research is to computationally find and validate novel inhibitors targeting these llm genes to combat S. aureus infections. An in-silico investigation was done using a complete literature review on NCBI and genomic analysis to uncover the llm genes in the S. aureus genome. Using computational techniques, including molecular docking using AutoDock Tools and PERL, twenty-two ligands, including the standard drug (Tunicamycin), were docked against the active site of the llm gene-encoded protein receptor. Pharmacokinetic investigations and molecular docking studies showed six potential inhibitors: ZINC06605913, ZINC06905586, ZINC35022243, ZINC40483738, ZINC90417652, and ZINC85428484. Molecular dynamics simulations (MDS) using GROMACS were performed on the molecules (ZINC90417652) with the highest binding affinity to examine the dynamics and stability of the protein-ligand complex. The predicted inhibitor demonstrated good pharmacological and structural properties, underscoring it’s potential as an effective antibacterial medications compare to tunicamycin. This study underscores the effectiveness of computational techniques in the identification and validation of novel inhibitors, providing a firm platform for the development of new antimicrobial medications targeting the llm genes in Staphylococcus aureus.
Targeting de novo purine biosynthesis for tuberculosis treatment
Authors: Lamprecht Dirk , Wall Richard , Davies Cadi , Pearson William , Davis Ellie , Willcocks Sam , Dallow John , Leemans Annelies , Wetzel Jennefer , Daems Stijn , Sancheti Pavankumar , Monshouwer Mario , Aguilar-Pérez Clara , Koul Anil , Sprangers Joke , Fiogbe Patricia , Saylock Samantha , Ricketts M. , Huff Adam , Grell Tsehai , Draghia-Akli Ruxandra , Lin Shiming , Gerber Michelle , Dhar Neeraj , Vos Ann , Roubert Christine , Sans Stéphanie , Desorme Amandine , Chappat Nicolas , Ray Aurélie , Clancy Kathleen , Everaerts Melissa , Esqui Jorge , Larrouy-Maumus Gerald , Fletcher Helen , Pym Alexander , Stoops Bart , Jackson Paul 
Published: September 2024

Abstract

Tuberculosis remains the leading cause of death from an infectious disease, responsible for 1.3 million deaths annually. Here, we report the discovery of a first-in-class small molecule inhibitor targeting PurF, the first enzyme in the mycobacterial de novo purine biosynthesis pathway. Our lead candidate, JNJ-6640, exhibited nanomolar bactericidal activity in vitro. Using an array of comprehensive genetic and biochemical approaches, we confirmed JNJ-6640 was highly selective for mycobacterial PurF compared to the human homologue. Single-cell level timelapse microscopy demonstrated PurF inhibition leads to a downstream impact on DNA replication. Proof-of-concept studies using a long-acting injectable formulation demonstrated the compound's in vivo efficacy. Finally, we show inclusion of JNJ-6640 could play a crucial role in improving the current treatment regimen for drug-resistant TB. Taken together, we demonstrate that JNJ-6640 is a promising chemical lead and show that targeting purine metabolism is a novel strategy for TB drug development.
Multisystem Inflammatory Syndrome and Severe COVID-19 in children have distinct metabolism pathways affected by pathogenic genetic variants.
Authors: Passetti Fabio , Urbanski Alysson , Freitas Flávia , Gomes Tiago , Schemberger Michelle , Reis Bárbara Carvalho Santos dos , de Carvalho Flavia Amêndola Anísio , Faccion Roberta Soares , Machado Lucas de Almeida , Santos Deborah Antunes dos , Cunha Daniela , Salú Margarida dos Santos , Moore Daniella Campelo Batalha Cox , Presibella Mayra Marinho , Noguchi Juliana , Borges Henrique , Tomiura Lais Kimie , de Castro Luiza Silva , Santos Letícia Graziela Costa , Silva Esdras Matheus Gomes da , Parreira Vinícius Da Silva Coutinho , Morello Luis , Marchini Fabricio , Tizzot Maria Regina , Ribas Mauricio Marcondes , Pascolat Gilberto , Ribas Carmen Australia , Vicente Fábio Fernandes da Rocha , Paschoal Alexandre , Cat Rubens , Carvalho Benilton , de Oliveira Jaqueline , Oliveira Marcus F. , Coutinho Luiz Lehmann , Nasr Acacia , Riediger Irina , Nardin Jeanine Marie , Mikami Liya Regina , Guimarães Ana Carolina Ramos , de Araujo-Souza Patricia Savio , Prata-Barbosa Arnaldo , Vasconcelos Zilton , Faoro Helisson , Santos Hellen Geremias dos 
Published: September 2024

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has triggered a global health crisis, with over 700 million confirmed cases and at least 7 million deaths reported by early 2024. Children are less vulnerable to severe SARS-CoV-2 infection than adults and typically experience milder respiratory symptoms. However, a rare but significant complication, known as multisystem inflammatory syndrome in children (MIS-C), can develop weeks after infection, characterized by a spectrum of inflammatory symptoms. This study employed whole-exome sequencing and over-representation analysis to identify distinct pathogenic genetic variants related to MIS-C or severe COVID-19 in a group of children with acute respiratory distress syndrome (ARDS), all of whom were unvaccinated for COVID-19. We observed an enrichment of pathogenic variants in genes related to carbohydrate metabolism, particularly glycogen breakdown, in severe COVID-19 pediatric patients, and in genes related to cholesterol and lipoprotein metabolism in MIS-C patients. These findings offer insights into the genetic underpinnings of MIS-C and severe COVID-19, suggesting potential genes and biological pathways for further research.
Orbital forcing of African hydroclimate over the past 800,000 years
Authors: Armstrong Edward , Tallavaara Miikka , Salonen Sakari , Camuera Jon , Kinyanjui Rahab , Valdes Paul 
Published: September 2024

Abstract

The African hydroclimate played a key role in shaping the evolutionary environment of numerous species including hominins. African precipitation is sensitive to insolation and is consequently strongly linked to Earth’s orbital variations. Here, we utilise singular spectrum analysis to extract key orbital frequencies from a range of proxy records and a climate model dataset generated using the HadCM3B-V1.0 model, to reveal key patterns of pan-African orbital forcing of hydroclimate variability over the past 800,000 years. The model and proxies show good agreement. Eccentricity modulated precession forcing is the dominant mode of variability in both proxies and model, driving enhanced summer monsoon precipitation across a North-South interhemispheric antiphase. The impact of eccentricity is complex and associated with precession modulation, direct insolation change, and indirect feedbacks linked to greenhouse gases and ice-sheet extent. Obliquity primarily influences the amplitude of precession forcing. Our results suggest that the combination of different orbital forcings created complex spatio-temporal precipitation patterns, and consequent ecosystem dynamics in Africa.
Comparison of the interpretation of ambiguity and aesthetic impression toward haiku poetry between experts and novices
Authors: Hitsuwari Jimpei , Nomura Michio 
Published: September 2024

Abstract

Haiku, the world’s shortest form of poetry, has usually been deemed ambiguous owing to its length. However, studies have shown that ambiguity lowers the aesthetic evaluation of a haiku, which contradicts the belief that ambiguity is a characteristic of both the haiku and art in general. One reason for this contradiction may be the interaction with the readers’ attributes, in particular, their expertise—a theme considered important in the field of aesthetic psychology. Therefore, in this study, we had 20 experts and 20 novices evaluate 20 low- and 20 high-ambiguity haikus, which another group of novices had evaluated and distinguished in the pilot study. The results revealed that the novices exhibited a lower liking for high-ambiguity haikus, whereas the experts demonstrated the same degree of liking for both high- and low-ambiguity haikus. Additionally, the experts had lower perceived ambiguity for high-ambiguity haikus than novices. This suggests a higher degree of liking for ambiguous haikus than novices because they were able to process them more fluently based on their knowledge and experiences. Furthermore, interest mediated the relationship between perceived ambiguity and liking among experts only. In sum, the experts appreciated ambiguous haikus in different ways compared to the novices. The results have implications for the psychology and cognitive science of aesthetics and art, where ambiguity is important, as well as for expertise in school education, where haiku is part of the curriculum.
Quantum Dots Functionalized Polymeric Nanoparticles as Cancer Theranostics: An Advanced Nanomedicine Strategy
Authors: Panchal Honey , Panjwani Drishti , Patel Shruti , Ahlawat Priyanka , Patel L.D. , Dharamsi Abhay , Patel Asha 
Published: September 2024

Background:
Cancer is a life-threatening disease prevalent worldwide, but its proper treatment has not yet been developed. Conventional therapies, like chemotherapy, sur-gery, and radiation, have shown relapse and drug resistance. Nanomedicine comprising cancer theranostics based on imaging probes functionalized with polymeric nanoconjugates is acquir-ing importance due to its targeting capability, biodegradability, biocompatibility, capacity for drug loading, and long blood circulation time. The application of synthetic polymers contain-ing anti-cancer agents and functionalizing their surface amenities with diagnostic probes offer a nano-combinatorial model in cancer theranostics.

Objective:
This study aimed to highlight the recent advancements in quantum dots-functionalized nanoconjugates and substantial progress in advanced polymeric nanomaterials in cancer theragnostics.

Methods:
This review details the synthetic methods for fabricating Quantum Dots (QDs) and QDs-functionalized polymeric nanoparticles, such as the hydrothermal method, solvothermal technique, atomic layer desorption, electrochemical method, microwave, and ultrasonic method.

Results:
Conjugating nanoparticles with photo-emitting quantum dots has shown efficacy for real-time monitoring and treating multi-drug-resistant cancer.

Conclusion:
Quantum dots are used in phototherapy, bioimaging, and medication delivery for cancer therapy. Real-time monitoring of therapy is possible and multiple models of hybridized quantum dots may be created to treat cancer. This review has discovered that numerous at-tempts have been made to conjugate carbon and graphene-based quantum dots with various biomolecules.
Identification of Method-Induced Artifacts and Light Chain C-terminal Extension Sequence Variants in Therapeutic Monoclonal Antibodies by Complementary Analytical Methods
Authors: Sun Qiang , Tong Ruinian , Li Yiqing , Wang Yu , Fang Feng , Jin Xionghua , Zhang Min , Xu Steven , Lei Run , Fan Pengcheng 
Published: September 2024

Background:
Atypical peaks were observed in capillary electrophoresis with sodium
dodecyl sulfate (CE-SDS) during the development of therapeutic monoclonal IgG4 antibodies
(mAb-X). Based on the previous literature reports, the atypical peak may be caused by various factors
such as post-translational modifications (PTMs), method-induced artifacts, sample degradation
and sequence variants. Due to the high complexity structure of mAbs and the limitations of
CE-SDS, acquiring comprehensive profiling of atypical peaks has historically been challenging.

Objective:
Here we developed a strategy utilizing complementary analytical methods to identify
the cause of atypical peak.

Methods:
This strategy includes optimizing reduced CE-SDS method to evaluate artifacts induced
by the analytical method, excluding potential glycation modifications, and utilizing Liquid Chromatograph
Mass Spectrometer (LC-MS) to characterize mAb-X.

Results:
Our study demonstrates that the atypical peaks of mAb-X are a mixture of method-induced
artifacts and variants in the C-terminal extension sequence of the light chain.

Conclusion:
Strategy for complementary analytical methods tools helps to identify the cause of
unknown species and plays a key role in product and process characterization.
Biological Mechanisms of Polyphenols against Clostridium Difficile: A Systematic Review
Authors: Darvishi Mohammad , Rafsanjani Seyed Mahmoud Reza Hashemi , Nouri Majid , Abbaszadeh Saber , Heidari-Soureshjani Saeid , Kasiri Karamali , Rahimian Ghorbanali 
Published: September 2024

Background:
Clostridium difficile is an opportunistic infection that can lead to antibi-otic-associated diarrhea and toxic megacolon.

Objective:
This systematic review study aimed to investigate polyphenols' antibacterial and anti-toxin properties and their effects on reducing complications related to C. difficile Infections (CDI).

Methods:
This systematic review was conducted following the PRISMA guideline 2020. Multiple databases, including Web of Science, PubMed, Cochrane Library, EMBASE, and Scopus, were searched thoroughly for existing literature. After considering the inclusion and exclusion criteria for the review, 18 articles were included. Data were collected and registered into an Excel file for further investigations and conclusions.

Results:
Polyphenols by reducing Reactive Oxygen Species (ROS) levels, increasing inflammatory factor Interleukin 10 (IL-10), reducing Nuclear Factor kappa B (NF-κB) and Tumour Necrosis Fac-tor-α (TNF-α), IL-6, IL-1α, IL-1β, Granulocyte Colony-stimulating Factor (G-CSF), and Monocyte Chemoattractant Protein-1 (MCP-1) and Macrophage Inflammatory Protein-1 alpha (MIP-1α) lev-els, and regulating the expression of Bcl-2 and Bax, make the growth and replication conditions of C. difficile more difficult and prevent it from producing toxins. Furthermore, polyphenols can ex-hibit prebiotic properties, promoting the growth of beneficial Bifidobacterium and Lactobacillus species and consequently regulating gut microbiota, exerting antimicrobial activities against C. dif-ficile. They also induce their beneficial effects by inhibiting the production of C. difficile TcdA and TcdB.

Conclusion:
Polyphenols have been reported to inhibit C. difficile growth and toxin production by several mechanisms in preclinical studies. However, more clinical studies are needed to investigate their safety in humans.
Mechanical and Microstructural Investigation on Friction Stir Welded Aluminium – Steel Dissimilar Joints
Authors: Sahu Santosh Kumar , Kumar B.R. Senthil , Parambil Bineesh Chulli , S Ravikumar , Vagdevi K , Natarajan K.K. , Nayak Bijaya Bijeta , Malayan Sumesh 
Published: September 2024

aims:
In this work an attempt was made to join aluminium alloy with the steel utilizing the friction stir welding process. During FSW, the tool travels through the propagation and dispersion of heat input per unit distance.

background:
Therefore, the quantity of heat input per unit of weld length is influenced by traversal speed. Heat is created because the tool spends less time spinning at extremely fast traversal speeds.

objective:
The materials are incorrectly mixed and compacted as a result, which reduces their strength. When the tool was moving rapidly, it generated enough heat at the right temperature to encourage grain growth and strain relief, increasing the impact strength of the joint.

method:
Micro-hardness varies over a distance in different zones depends on the grain size and phases underneath each depression. Micro-hardness often rises as a result of grain refining brought on by tool rotation in the SZ and TMAZ.

result:
But as the indentation distance from the SZ grows, the micro-hardness declines, especially in the HAZ and the BM&amp;#039;s grain-coarsened region.

conclusion:
The distribution of micro-hardness also shows that dynamic recrystallization in the FSW leads to considerable grain refinement in the SZ. SZ is hence harder on the microscale than BM and HAZ.

other:
The various mechanisms such as climb, cross-slip and annihilation, causes rearrangement of dislocations and results in the formation of low angle grain boundaries and development of sub-grains were observed in micrograph.
Pengaruh Brand Awareness Sebagai Variabel Pemasaran Media Sosial Terhadap Minat Beli Konsumen
Authors: Annora Gea Cinta Endy , Prabandari Sri Palupi 
Published: September 2024

The era of rapid business development requires entrepreneurs to provide their best products in the competition. The increasing competition in the business has triggered businesspeople to join in a race of product development. Endy’s Luck offers a distinct way of enjoying snake fruit, that is by presenting it as fudgy brownies. As the brand is still new, massive marketing efforts are needed. The objective of this quantitative research is to analyze the effects of social media marketing on consumer’s intention to purchase snake fruit’s processed products with brand awareness as the mediating variable. Using non-probability sampling method and purposive sampling technique, 85 people with Instagram accounts who have seen the profile of Endy’s Luck’s Instagram account were selected as the respondents. The results of the data analysis in SPSS 26 indicate that social media marketing significantly influences brand awareness and purchase intention, that brand awareness significantly affects purchasing intention, and that brand awareness mediates the impact of social media marketing on consumer’s purchase intention.

Abstrak
Era perkembangan bisnis yang sangat pesat mengharuskan para pelaku bisnis memberikan produk yang terbaik dalam persaingan. Semakin ketatnya persaingan dalam bisnis, memicu pelaku bisnis berlomba-lomba dalam mengembangkan bisnisnya. Endy’s Luck menawarkan cara lain untuk menikmati buah salak dalam sebuah produk makanan berupa fudgy brownies. Merek Endy’s Luck yang tergolong baru mengharuskan bisnis ini untuk melakukan pemasaran yang masif. Tujuan penelitian ini adalah untuk menganalisis pengaruh pemasaran media sosial terhadap minat beli konsumen dengan brand awareness sebagai variabel mediasi pada produk olahan salak. Jenis penelitian dalam penelitian ini adalah kuantitatif. Menggunakan non probability sampling dengan teknik purposive sampling, responden sebanyak 85 dipilih dengan kriteria yang memiliki dan menggunakan media sosial Instagram, serta pernah melihat profil dari akun media sosial Instagram dari Endy’s Luck. Hasil dari analisis data menggunakan SPSS 26 menyatakan bahwa pemasaran media sosial berpengaruh signifikan terhadap brand awareness dan minat beli konsumen. Selain itu, brand awareness juga berpengaruh signifikan terhadap minat beli. Terakhir, hasil penelitian menunjukkan bahwa brand awareness memediasi pengaruh antara pemasaran media sosial terhadap minat beli konsumen.