bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-variable integration with a variational quantum circuit
Authors: Cruz-Martinez Juan M , Robbiati Matteo , Carrazza Stefano 
Published: June 2024

Abstract
In this work we present a novel strategy to evaluate multi-variable integrals with quantum circuits. The procedure first encodes the integration variables into a parametric circuit. The obtained circuit is then derived with respect to the integration variables using the parameter shift rule technique. The observable representing the derivative is then used as the predictor of the target integrand function following a quantum machine learning approach. The integral is then estimated using the fundamental theorem of integral calculus by evaluating the original circuit. Embedding data according to a reuploading strategy, multi-dimensional variables can be easily encoded into the circuit’s gates and then individually taken as targets while deriving the circuit. These techniques can be exploited to partially integrate a function or to quickly compute parametric integrands within the training hyperspace.
Intelligent pesticide recommendation system for cocoa plant using computer vision and deep learning techniques
Authors: Arakeri Megha , M P Dhatvik , Kavan A V , Murthy Kamma Sushreya , Nishitha Nagineni Lakshmi , Lakshmi Napa 
Published: June 2024

Abstract
Agriculture in India is a vital sector that contains a major portion of the population and impacts substantially the country’s economy. Cocoa is a crop that has commercial importance and is used for the production of chocolates. It is one of the main crops cultivated in south India due to the humid tropical climate. However, the cocoa plant is susceptible to various diseases caused by bacteria, viruses, and pests resulting in yield losses. Visual analysis is a subjective and time-consuming process. Further, farmers use improper pesticides to prevent diseases, and this will degrade the plant and soil quality. To overcome these problems, this paper proposes an automatic cocoa plant disease detection and pesticide recommendation system using computer vision and deep learning techniques. The proposed system was evaluated on several cocoa plant images, and an accuracy of 97.36% was obtained in disease classification. The proposed system can help cocoa farmers in the detection of cocoa plant diseases in the early stage and reduce the use of excessive pesticides, thus promoting sustainable agriculture practices.
Implementation of exact thermal analysis in extended Oxley’s predictive machining theory
Authors: Dubey Aakash , Lalwani Devdas 
Published: June 2024

Abstract
Finding the exact solution to the generated temperatures that are more closely aligned with the actual nature of the process is important while conducting analytical modeling of the chip formation process in metal cutting. The extended Oxley’s predictive machining theory is implemented with the exact thermal analysis approach. This study presents temperature distributions near the shear plane on the workpiece side along with an exact temperature prediction for orthogonal cutting using the Komanduri-Hou model for the shear plane heat source. An explicit solution is also derived to obtain the tool-chip interface temperatures. The intricate formulae utilized in the original research study of Komanduri-Hou are solved using MATLAB code. The approach used here makes it easier to use the exact solution in future research for various categories of materials. The temperature distribution plots help to clarify the metal-cutting procedure and understand the different heat zones. The outcomes of shear angle, forces, stresses, strains, strain rates, and average temperatures are consistent with those reported in earlier studies.
Electro-thermal and mechanical property analysis of powder metallurgy processed, multi-stage ball milled aluminium-copper-multi walled carbon nanotube composite
Authors: Kundu Subham , Mondal Subhas Chandra 
Published: June 2024

Abstract
Aluminium Metal Matrix Composite (Al-MMC) is a favourable option for industries like automotive, aerospace, sports equipment, electronic packaging and renewable energy because of its impressive strength-to-weight ratio, effective thermal and electrical conductivity, abundant availability and reasonable cost of aluminium. Carbon nanotube (CNT) reinforced Al-MMC is popular among researchers due to its impressive strength and stiffness. The electrical and thermal conductivity of Al-CNT is a less focused field with challenges like uniform dispersion and structural integrity of CNT depending on the manufacturing process. In this paper, a novel method of Multistage ball milling (MSBM) was introduced to develop a powder metallurgy processed Al-MMC, consisting of 5-weight percentage (5 wt%) of copper (Cu) and 0.5 to 1.5 volume percentage (0.5–1.5 vol%) multi-walled carbon nanotubes (MWCNT). In MSBM, mixing was done in two stages with two different rpms of the ball mill to add the advantages of flake powder metallurgy with lower chances of structural damage and the agglomeration of CNT. Mechanical, electrical, thermal, and microstructure characteristics of the fixed-speed single-stage ball milling (SSBM) process and the MSBM were compared. MSBM-processed Al-5Cu-0.5CNT composites showed higher electrical conductivity (15.03%), thermal conductivity (5.88%) and hardness (9.68%) than SSBM-processed composites. Al-5Cu-0.5CNT developed by the MSBM process achieved superior electrical and thermal conductivity, surpassing pure sintered Al by 138.45% and 9.39%, respectively.
HLG-YOLOv7: small object detection in conveyor belt damage based on leveraging hybrid local and global features
Authors: Wang Gongxian , Yue Qiang , Sun Hui , Tian Yu , Wang Yueyin , Zhou Qiao 
Published: June 2024

Abstract
In the industrial production process, the detection of conveyor belt damage plays a crucial role in ensuring the stable operation of the transportation system. To tackle the issues of significant changes in damage size, missed detections, and poor detection ability of small-size objects in conveyor belt surface damage detection, an improved HLG-YOLOv7 (Hybrid Local and Global Features Network) conveyor belt surface defect detection algorithm is proposed. Firstly, Next-VIT is employed as the backbone network to fully extract local and global features of the damage, enhancing the model’s ability to extract features of different-sized damages. Additionally, to deeply utilize the extracted local and global features, the Explicit Visual Center (EVC) feature fusion module is introduced to obtain comprehensive and discriminative feature representations, further enhancing the detection capability of small objects. Lastly, a lightweight neck structure is designed using GSConv to reduce the complexity of the model. Experimental results demonstrate that the proposed method has better small object detection performance compared to existing methods. The improved algorithm achieves mAP and F1 scores of 96.24% and 97.15%, respectively, with an FPS of 28.2.
Fabrication of tips for scanning probe magnetometry by diamond growth
Authors: Götze Arne , Vidal Xavier , Lang Nicola , Giese Christian , Quellmalz Patricia , Jeske Jan , Knittel Peter 
Published: June 2024

Abstract
The use of quantum sensors is promising detailed insights into physical phenomena such as magnetism or superconductivity. One example of such quantum sensors is a microscopic diamond tip containing nitrogen vacancy (NV) centers, which is capable of producing correlated measurements of vectorial magnetic fields and the sample topography on the nanoscale. In this study, we present a chemical vapor deposition (CVD) process to produce diamond tips with NV centers by overgrowing microstructured diamond substrates. The resulting diamond tips exhibit a radius of curvature of approximately 10 nm, suitable for use as a probe in an atomic force microscope. The magnetic sensitivity of the CVD-grown diamond tips is characterized with pulsed measurements of the optically detected magnetic resonance, which yield a minimum magnetic sensitivity of 60 µT

Hz

−
1

. The growth of the diamond microstructures is observed to differ from the commonly used geometric model predicting CVD growth of bulk diamond crystals. We identify an empirical model for the growth behavior of the microstructures by taking into account processes described in the step flow growth model for crystals. Additionally, we demonstrate the applicability of the developed CVD growth process to membrane substrates required for the preparation of magnetometry-capable diamond tips.
Large values of quadratic Dirichlet 𝐿-functions over monic irreducible polynomial in 𝔽_{𝕢}[𝕥]
Authors: Darbar Pranendu , Maiti Gopal 
Published: June 2024

We prove an

Ω
\Omega

-result for the quadratic Dirichlet

L
L

-function

|

L
(
1

/

2
,

χ
P

)

|

|L(1/2, \chi _P)|

over irreducible polynomials

P
P

associated with the hyperelliptic curve of genus

g
g

over a fixed finite field

F

q

\mathbb {F}_q

in the large genus limit. In particular, we showed that for any

ϵ
∈
(
0
,
1

/

2
)

\epsilon \in (0, 1/2)

,
\[

max

P
∈

P

2
g
+
1

|

L
(
1

/

2
,

χ
P

)

|

≫
exp
⁡

(

(

(
1

/

2
−
ϵ
)

ln
⁡
q

+
o
(
1
)
)

g

ln
2

⁡
g

ln
⁡
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)

,

\max _{\substack {P\in \mathcal {P}_{2g+1}}}|L(1/2, \chi _P)|\gg \exp \left (\left (\sqrt {\left (1/2-\epsilon \right )\ln q}+o(1)\right )\sqrt {\frac {g \ln _2 g}{\ln g}}\right ),

\]
where

P

2
g
+
1

\mathcal {P}_{2g+1}

is the set of all monic irreducible polynomials of degree

2
g
+
1

2g+1

. This matches with the order of magnitude of the Bondarenko–Seip bound.
Effect of Interaction Between Vitamin D and Serum Uric Acid on Hypertension in Adults
Authors: Qianqian Wang , Xinlei Miao , Guimin Tang , Manling Hu , Shuang Liu , Xiangjun Niu , Wan Zhao , Song Leng 
Published: June 2024

Abstract

OBJECTIVE
To investigate whether the interaction between serum vitamin D and serum uric acid has an effect on blood pressure.

METHODS
A cross-sectional study was conducted with 7,951 subjects selected from the health management center of the Second Hospital of Dalian Medical University during 1 January 2020 and 30 September 2022. The dose–response relationship between serum vitamin D, blood uric acid, and blood pressure was analyzed using restricted cubic spline. The relationship between each variable and elevated blood pressure was analyzed using multifactorial analysis in a generalized additive model and combined with a multiplicative–additive hierarchical interaction model to explore the effects of the interaction of serum vitamin D and blood uric acid on elevated blood pressure.

RESULTS
The mean age of the study population was (42.61 ± 11.17) years and the detection rate of hypertension was 12.14% (965/7,951). The risk of elevated blood pressure (high-normal blood pressure + hypertension) decreased with increasing serum vitamin D concentration, but the risk of elevated blood pressure increased with increasing serum uric acid levels. Compared with those with adequate serum vitamin D and normal blood uric acid, the odds ratio (OR) for the risk of high-normal blood pressure was 1.54 [95% confidence interval, CI (1.22, 1.94), P &lt; 0.001] and the OR for the risk of hypertension was 3.17 [95% CI (2.13, 4.72), P &lt; 0.001] for those with inadequate serum vitamin D and high blood uric acid. The risk of elevated blood pressure was highest when serum 25-hydroxyvitamin D was less than 25 nmol/l and blood uric acid was higher than 600 µmol/l.

CONCLUSIONS
The interaction between serum vitamin D and blood uric acid has an effect on elevated blood pressure. The risk of hypertension was maximized when serum vitamin D was insufficient and blood uric acid was high.
The role of imagination in protest
Authors: Devraj Megha 
Published: June 2024

Abstract
Recent literature on social movements assigns a central role to the imagination. One way for activists to further their aims is through dramatic, confrontational acts of protest. I argue that transcendent imagining is key to understanding what protest does qua act of speech. A common approach to protest sees it as a speech act of condemning some feature of the socio-political world and appealing for change. While this is a helpful general template for what vocal dissent is, it is insufficient to explain what gives protests their political power. Specifically, it overlooks the fact that effective protests usually create a theatrical spectacle of norm breaking. Displays of defiance lift a constraint on how we imagine our socio-political world, and so allow us to begin reshaping it.
scVIC: deep generative modeling of heterogeneity for scRNA-seq data
Authors: Xiong Jiankang , Gong Fuzhou , Ma Liang , Wan Lin 
Published: June 2024

Abstract

Motivation
Single-cell RNA sequencing (scRNA-seq) has become a valuable tool for studying cellular heterogeneity. However, the analysis of scRNA-seq data is challenging because of inherent noise and technical variability. Existing methods often struggle to simultaneously explore heterogeneity across cells, handle dropout events, and account for batch effects. These drawbacks call for a robust and comprehensive method that can address these challenges and provide accurate insights into heterogeneity at the single-cell level.

Results
In this study, we introduce scVIC, an algorithm designed to account for variational inference, while simultaneously handling biological heterogeneity and batch effects at the single-cell level. scVIC explicitly models both biological heterogeneity and technical variability to learn cellular heterogeneity in a manner free from dropout events and the bias of batch effects. By leveraging variational inference, we provide a robust framework for inferring the parameters of scVIC. To test the performance of scVIC, we employed both simulated and biological scRNA-seq datasets, either including, or not, batch effects. scVIC was found to outperform other approaches because of its superior clustering ability and circumvention of the batch effects problem.

Availability and implementation
The code of scVIC and replication for this study are available at https://github.com/HiBearME/scVIC/tree/v1.0.
MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis
Authors: Wang Lexiang , Zhou Jingli , Wang Xuan , Wang Yadong , Li Junyi 
Published: June 2024

Abstract

Motivation
Accurately predicting the driver genes of cancer is of great significance for carcinogenesis progress research and cancer treatment. In recent years, more and more deep-learning-based methods have been used for predicting cancer driver genes. However, deep-learning algorithms often have black box properties and cannot interpret the output results. Here, we propose a novel cancer driver gene mining method based on heterogeneous network meta-paths (MCDHGN), which uses meta-path aggregation to enhance the interpretability of predictions.

Results
MCDHGN constructs a heterogeneous network by using several types of multi-omics data that are biologically linked to genes. And the differential probabilities of SNV, DNA methylation, and gene expression data between cancerous tissues and normal tissues are extracted as initial features of genes. Nine meta-paths are manually selected, and the representation vectors obtained by aggregating information within and across meta-path nodes are used as new features for subsequent classification and prediction tasks. By comparing with eight homogeneous and heterogeneous network models on two pan-cancer datasets, MCDHGN has better performance on AUC and AUPR values. Additionally, MCDHGN provides interpretability of predicted cancer driver genes through the varying weights of biologically meaningful meta-paths.

Availability and implementation
https://github.com/1160300611/MCDHGN
GenoFig: a user-friendly application for the visualization and comparison of genomic regions
Authors: Branger Maxime , Leclercq Sébastien O 
Published: June 2024

Abstract

Motivation
Understanding the molecular evolutionary history of organisms usually requires visual comparison of genomic regions from related species or strains. Although several applications already exist to achieve this task, they are either too old, too limited, or too complex for most user’s needs.

Results
GenoFig is a graphical application for the visualization of prokaryotic genomic regions, intended to be as easy to use as possible and flexible enough to adapt to a variety of needs. GenoFig allows the personalized representation of annotations extracted from GenBank files in a consistent way across sequences, using regular expressions. It also provides several unique options to optimize the display of homologous regions between sequences, as well as other more classical features such as sequence GC percent or GC-skew representations. In summary, GenoFig is a simple, free, and highly configurable tool to explore the evolution of specific genomic regions in prokaryotes and to produce publication-ready figures.

Availability and implementation
Genofig is fully available at https://forgemia.inra.fr/public-pgba/genofig under a GPL 3.0 license.
MetaboReport: from metabolomics data analysis to comprehensive reporting
Authors: Dong Yonghui , Malitsky Sergey 
Published: June 2024

Abstract

Motivation
Metabolomics, as an essential tool in systems biology, is now widely accessible to researchers of all levels. Yet challenges remain in data analysis and result interpretation. To address these challenges, we introduced MetaboReport, a versatile and interactive web app that simplifies metabolomics experiment design, data preprocessing, exploration, statistical analysis, visualization, and reporting.

Results
MetaboReport produces a comprehensive HTML report, including project details, an introduction, interactive plots and tables, statistical results and an in-depth explanations and interpretation of the results. MetaboReport is particularly tailored for research labs and metabolomics core facilities that provide metabolomics services, allowing them to efficiently manage and document different metabolomics projects, and effectively report the metabolomics results to users.

Availability and implementation
MetaboReport is freely accessible on https://metaboreport.com, with source code available on GitHub (https://github.com/YonghuiDong/MetReport). Alternatively, users can install MetaboReport as a standalone desktop app (https://metaboreport.sourceforge.io).
Gene expression landscape of cutaneous squamous cell carcinoma progression
Authors: Bencomo Tomas , Lee Carolyn S 
Published: June 2024

Abstract

Background
Cutaneous squamous cell carcinomas (cSCCs) are the second most common human cancer and have been characterized by RNA sequencing (RNA-Seq); however, the transferability of findings from individual studies may be limited by small sample sizes and diverse analysis protocols.

Objectives
To define the transcriptome landscape at different stages in the progression of normal skin to cSCC via a meta-analysis of publicly available RNA-Seq samples.

Methods
Whole-transcriptome data from 73 clinically normal skin samples, 46 actinic keratoses (AK) samples, 16 in situ SCC samples, 13 keratoacanthoma (KA) samples and 147 cSCC samples [including 30 samples from immunocompromised patients and 8 from individuals with recessive dystrophic epidermolysis bullosa (RDEB)] were uniformly processed to harmonize gene expression. Differential expression, fusion detection and cell-type deconvolution analyses were performed.

Results
Individual RNA-Seq studies of cSCC demonstrated study-specific clustering and varied widely in their differential gene expression detection. Following batch correction, we defined a consensus set of differentially expressed genes (DEGs), including those altered in the preinvasive stages of cSCC development, and used single-cell RNA-Seq data to demonstrate that DEGs are often – but not always – expressed by tumour-specific keratinocytes (TSKs). Analysis of the cellular composition of cSCC, KA and RDEB-cSCC identified an increase in differentiated keratinocytes in KA, while RDEB-cSCC contained the most TSKs. Compared with cSCC arising in immunocompetent individuals, cSCC samples from immunosuppressed patients demonstrated fewer memory B cells and CD8+ T cells. A comprehensive and unbiased search for fusion transcripts in cSCC and intermediate disease stages identified few candidates that recurred in &gt;1% of all specimens, suggesting that most cSCC are not driven by oncogenic gene fusions. Finally, using Genotype-Tissue Expression (GTEx) data, we distilled a novel 300-gene signature of chronic sun exposure that affirms greater cumulative ultraviolet (UV) exposure in later stages of cSCC development.

Conclusions
Our results define the gene expression landscape of cSCC progression, characterize cell subpopulation heterogeneity in cSCC subtypes that contribute to their distinct clinical phenotypes, demonstrate that gene fusions are not a common cause of cSCC and identify UV-responsive genes associated with cSCC development.
Differences Between the 2016 and 2022 Food and Drug Administration Guidance—Implications for Design and Interpretation of Clinical Trials in Ulcerative Colitis
Authors: Hanzel Jurij , Ma Christopher , Peyrin-Biroulet Laurent , Danese Silvio , Sands Bruce E , Jairath Vipul 
Published: June 2024

AbstractBackgroundIn 2022, the Food and Drug Administration (FDA) updated its draft guidance for drug development in ulcerative colitis, replacing the version from 2016. Several changes from the 2016 version merit further discussion as they impact clinical trial design and the interpretation of trial results.MethodsWe compared both documents and critically appraised the changes and implications for future clinical trials.ResultsThe 2022 guidance recommends full colonoscopy, rather than flexible sigmoidoscopy, to document disease activity in all involved segments of the colon. The concordance between the findings of the 2 procedures is very high and there is little evidence to support colonoscopy over sigmoidoscopy. The use of colonoscopy, rather than sigmoidoscopy, is also associated with a higher burden to trial participants who must undergo full bowel preparation, cost, and a potential for more adverse events. The definition of the Mayo endoscopic score of 0 was changed from the original publication to “normal appearance of mucosa,” which suggests that endoscopic signs of prior disease, such as pseudopolyps and scarring, are incompatible with a score 0, even though they are not associated with active disease. The term “mucosal healing” has been abolished and histologic outcomes defined as exploratory. A welcome change is that shorter washout periods than 5 half-lives will be considered to reduce patient exposure to corticosteroids as bridging therapy.ConclusionsThe 2022 FDA draft guidance includes changes which for the most part are not informed by empirical evidence, which may ultimately complicate interpretation of future trials and preclude comparisons with past trials.