bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine and Deep Learning Approaches for Plant Disease Detection: A Comprehensive Review
Authors: Yogesh V. Chimate Et al. 
Published: February 2024

People have been using edible foods since ancient times, and they continue to be an essential component of a healthy diet and traditional food systems today. Food crops as a major source of human energy intake, and the challenges they face due to biotic and abiotic stress factors, such as pollution, insects, bacteria, and unfavourable weather conditions. Detecting plant diseases in the early stage is critical for ensuring a stable supply of healthy food, and traditional methods of disease detection by experts are lengthy and have some limitations. The use of Machine and Deep learning is a key aspect of precision farming for crop growth monitoring. Plenty ML strategies, including random forest and support vector machines (SVMs), Convolutional Neural Networks, Deep learning as well as image processing have been used to precisely detect, classify, and predict plant diseases. By leveraging machine learning algorithms, farmers and agricultural experts can accurately detect and diagnose crop diseases, enabling them to take appropriate measures to control and prevent further spread of the disease. This article provides a comprehensive overview of the different AI approaches for plant disease identification and control, drawing on a range of research articles in the field. The application of machine learning in agriculture holds promise for improving crop health and increasing yields and represents an important area of innovation for sustainable agriculture in the future.
Functional Brain Connectivity Differences between Aphasic and Neurotypical Brains
Authors: Kailash Nath Tripathi Et al. 
Published: February 2024

Aphasia is a language disorder that can arise from brain damage, leading to difficulties in understanding, generating, or using language. Although the precise neural mechanisms are not fully elucidated, it is hypothesized that these disruptions involve altered communication and interaction among brain regions. In this study, functional magnetic resonance imaging (fMRI) was employed to assess functional connectivity in both individuals with aphasia and neurotypical individuals. Functional connectivity is a measure of the way that brain regions communicate and interact with each other. The study participants performed a series of language-processing tasks, while their fMRI data was collected. The study's findings showed that individuals with aphasia had unique functional brain connectivity patterns when compared to neurotypical individuals. These distinctions were most prominent in the left hemisphere, which is conventionally associated with language processing. In particular, individuals with aphasia demonstrated diminished functional connectivity between the language regions in the left hemisphere and other brain regions, including those in the right hemisphere and the frontal lobe. The study's findings suggest that differences in functional brain connectivity may contribute to language deficits in aphasia. The study's findings also hold significant implications for advancing our understanding of the neurological underpinnings of aphasia and the potential for improved diagnostic and therapeutic methods for individuals with this condition.
“Shopper Mindfulness and Acuity Near Green Marketing in India”
Authors: Arjunsinh Rajput Et al. 
Published: February 2024

Green marketing is the advertising of crops that are supposed to be ecologically benign. It joins a comprehensive series of doings including creation alteration, vagaries to the making development, justifiable wrapper as well as changing advertisement. Thus, green selling refers to full selling concept that making, eating and discarding of foods and facilities chance in a routine that is less injurious to the location with emergent alertness about the implication of global warming, non-biodegradable solid surplus, detrimental power of toxins, etc. both sellers and users are pretty increasingly subtle to the need for green products and services.
While the shift of ‘green’ may seem to be luxurious in short run, it will prove to be essential and useful in the long run. This study is essential to classify whether the customers in India are aware of green marketing and green foodstuffs. It classifies the general ecological beliefs of customers. It inspects the factors moving procurement performance of customers for green crops. It focuses the reasons which make the customers keen to pay for green products. For this purpose, primary data were collected from 150 sample respondents using a well – structured survey. Boards were used to analyse the data and use Desks, humble proportions to take it.
Design and Simulation of Resilient RF Receivers for 5G Interference Mitigation Using MATLAB
Authors: Shatha Kareem Abbas Et. al 
Published: February 2024

Introduction: Advanced terminal capabilities increase mobile broadband traffic, straining spectrum resources. Traditional methods like base stations are expensive. Heterogeneous networks (HetNets) using pico cells attempt to improve efficiency, however interference persists. A suggested mitigation technique uses the modified greatest weighting delay first (MLWDF) algorithm for resource allocation and reception processing, which performs well in simulations. Space, time, frequency, time-frequency, and coding domain interference reduction methods are investigated, each having hardware requirements and restrictions.
Aim and objectives: The study uses MATLAB to construct and simulate robust RF receivers. Enhancing 5G communication network interference reduction is the goal.
Method: Simulink is used to study transmitter and receiver RF losses, including I/Q imbalances, phase noise, and power amplifier non-linearity. Spectrum masks, error vector magnitudes, and peaks-to-average power ratios measure performance. Simulink models examine constellation distortion, neighboring channel rejection, and packet error rates in 802.11ax and 5G waveform reception due to RF impairments. The paper stresses the necessity of reliable data measurement for RF interference analysis and discusses interference mitigation.
Results: Comparing Error Vector Magnitudes (EVMs) in Case 1 and Case 2 shows how NR interference affects HE receptions. EVMs approach -20 dB in Case 1 without NR interference. In Case 2, NR interference distorts constellations and lowers EVMs to -17 dB, suggesting poor reception. ACRs demonstrate NR-free channel separation by measuring power differences. The future investigation involves analyzing ACRs with HE waveforms as interferers and examining system behavior under different interference situations.
Conclusion: To reduce non-idealities in mobile communication transceivers, this thesis presents digital projection interpolation and Wiener-SAF for leakage route and receiver nonlinearity estimation.
Sort-term adaptations on bilateral body weight-bearing symmetry and postural control through the application of rotary prisms in healthy children
Authors: Ziaka Aikaterini , Giakas Ioannis , Tsaklis Panagiotis 
Published: February 2024

Background: Motor-control is organized by coordinated sensory systems which integrate for the preparation of movement. Certain visuoperceptive disorders may impair proper development of motor control during childhood, thereby impacting functional aspects like bilateral weight-bearing symmetry. Rotary prisms (RPs) are a rehabilitation modality that have shown promise in facilitating motor-control and spatial-realignment for adults, improving weight-bearing symmetry, often evaluated by indexes like the normalized symmetry index (NSI%). However, less is known for the short-term effect of RPs on NSI% and consequent effects on functional capacity in healthy children.
Methods: We evaluated the acute and short-term chronic effect of RPs in fourteen healthy children (8.8±1.1 years) on NSI% and the total execution time (s) of a dynamic balance sit-to-stand task (SITS). Measurements were performed at baseline, immediately following RP application (immediate phase) and 10 min following RP removal (spatial re-alignment).
Results: We detected an overall main effect of time on NSI% (F=15.1, p<0.001, η2=.54), improving both immediate (-67.3%, 3.4±4.46%, p<0.001) and spatial re-alignment phases (-55.3%, 5.2±4.3%, p<0.001) compared to baseline (9.7±1.9 %). Moreover, no significant differences for NSI% between immediate and spatial re-alignment phases were detected (p>0.05). However, TUT of the SITS task remained unaffected (F=1.13, p>0.05).
Conclusions: Non-significant differences for NSI% between immediate and spatial re-alignment phases indicate that short-term neural adaptations may persist following the removal of RPs in healthy children. Indicating the potential suitability of RPs in neurorehabilitation for children with balance impairments, such as pre-existing sensory motor dysfunctions and others.
Modeling the number of clothing merchandise returned through online shopping using a mixture of Poisson distribution: an interdisciplinary approach
Authors: Nain Anuj 
Published: February 2024

Background: Online shopping has witnessed a significant surge in popularity owing to its accessibility and convenience. The rise of online shopping has revolutionized the retail industry, with clothing purchases garnering a dedicated following. However, a persistent challenge in internet purchasing lies in the uncertainty surrounding the fit, appearance, and quality of clothing merchandise. As a result, customers often resort to returning items that fail to meet their expectations or differ from the website's descriptions. In this study, we aim to address this issue by proposing a novel approach to model the number of items returned through online purchases. Specifically, we employ a mixture of Poisson distribution to capture the complexities of the return process and its underlying factors.
Methods: A mixture of Poisson distribution is employed to model the uncertainties in online clothing returns. The approach aims to capture the complexities of the return process and its underlying factors, providing valuable insights for e-commerce businesses to optimize operations and enhance customer satisfaction.
Results: The findings of this study have the potential to shed light on the reasons behind increased return rates, offering e-commerce businesses valuable information to optimize their operations and enhance customer satisfaction.
Conclusions: Poisson distribution is capable of analyzing the hidden patterns in the data, and hence the results of the study are beneficial for various stakeholders, including statisticians, e-commerce firms, and app developers.
Remiksowanie iluzji. Krzysztofa Wieczorka droga od grafiki do malarstwa
Authors: Leśnikowski Dariusz 
Published: February 2024

Krzysztof Wieczorek, zmarły w 2021 roku łódzki artysta, był wybitnym grafikiem. W swoich poszukiwaniach twórczych ujawniał naturę dociekliwego współczesnego manierysty. W swoich pracach poddawał „obróbce” między innymi cytaty z obrazów i grafik Herculesa Seghersa. Fragmenty krajobrazów stworzonych przez holenderskiego twórcę uzupełniały pejzaże zakomponowane przez polskiego artystę.
Wieczorek dopełniał obraz dzięki różnym, graficznym i malarskim, ingerencjom. Zabiegi te zmierzały ku zróżnicowaniu odbitek z nakładu, dzięki czemu nabierały one charakteru unikatowego. Krzysztof Wieczorek wykorzystywał w swojej pracy wykonane wcześniej matryce, także ich fragmenty, zestawiając je w rozmaitych konfiguracjach. Możemy tu mówić o swoistym „remiksowaniu” artystycznych komunikatów. Wieczorek tworzył warianty obrazów, a nawet ich sekwencje. Sukcesywne modyfikowanie podłoża graficznego dokonywało się w dużej mierze poprzez złożone działania o charakterze malarskim.
W dziełach Wieczorka podkład stanowi zarówno jednorodna odbitka graficzna, jak i ich kolaż. Części składowe mogły być wykonane w akwaforcie, akwatincie, mezzotincie, suchej igle, czy pochodzić z wydruku komputerowego. Wybór techniki (lub technik), stopień destrukcji matrycy (dokonujący się na przykład poprzez chropowacenie, rytowanie i trawienie powierzchni) determinował do pewnego stopnia dalsze poczynania twórcy. Podobnie jak wykorzystanie kolorowych papierów do druku. Artysta eksperymentował także z podłożem, wykorzystując do swoich kompozycji powierzchnie płócienne, tekturowe czy drewniane. Podkład graficzny był poddawany zabiegom malarskim. Twórca kładł na powierzchni grafiki warstwę farby akwarelowej, olejnej czy akrylowej. Impregnował powierzchnie werniksami.
Istota poszukiwań podejmowanych przez Krzysztofa Wieczorka kryje się oczywiście w zachowania równowagi pomiędzy aspektami technicznymi i technologicznymi, a walorami estetycznymi dzieła oraz wyznaczanymi przez elementy świata przedstawionego treściami. W swoich poszukiwaniach twórca odnosił się do skomplikowanych relacji między tym, co graficzne, a tym, co malarskie. Szukał uniwersalnego, integralnego języka komunikacji wizualnej.
ANALYSIS OF HIGHLY POLAR PESTICIDES IN FOODS OF PLANT ORIGIN VIA LIQUID CHROMATOGRAPHY/MASS SPECTROMETRY
Authors: ARSLAN BURAK Deniz , ŞAHİN Yücel , BURAK Muhammet 
Published: February 2024

Pesticides in foods of plant origin are becoming a major issue due to their intensive use in agriculture. Since pesticides are potentially harmful to the environment and consequently to human health through the consumption of pesticide contaminated foods. The European Community and also the Ministry of Agriculture and Forestry in Turkish Republic established maximum residue levels (MRLs), based on the assumption that good agricultural practice is applied at the use of pesticides in farming, for pesticide residues in food of plant origin. As a consequence food commodities have to be controlled to assure the non-violation of the MRLs. Thus an appropriate control of their residues in samples has to be operated.
In this study, we inferred the analytical methods for highly polar pesticides in foods of plant origin via LC-MS/MS after extraction with acidified methanol according to QuPPe (Quick Polar Pesticides) method. Optimization of 13 highly polar pesticides was carried out with LC-MS/MS Q-Trap. After the optimization process has been completed, the samples to be taken according to the SANTE (Guidance document on analytical quality control and method validation procedures for pesticide residues and analysis in food and feed) guidelines have been carefully selected, including high water, high acid/high water, high sugar/low water, high oil/low water and high starch/low water content and difficult or unique commodities. Six samples carefully selected according to the SANTE guideline were carried out at two different concentrations, one of at the detection limit which is 10 µg/L. At the end of the studies, it was found that the RSD criteria for repeatabilitiy was below 20 % for all substances. In addition, the recovery value for all substances was in the range of 70 – 120 %. As a result, 13 different polar pesticides can be analyzed in product groups of plant origin via LC-MS/MS method developed by using hypercarb column.
Self-Localization of Guide Robots Through Image Classification
Authors: Alam Muhammad S. , Mohamed Farhan B. , Hossain AKM B. 
Published: February 2024

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accurate solution for indoor robot navigation. The more accurate solution of the guide robotic system opens a new window of the self-localization system and solves the more complex problem of indoor robot navigation. It makes a reliable interface between humans and robots. This study successfully demonstrated how a robot finds its initial position inside a room. A deep learning system, such as a convolutional neural network, trains the self-localization system as an image classification problem. The robot was placed inside the room to collect images using a panoramic camera. Two datasets were created from the room images based on the height above and below the chest. The above-mentioned method achieved a localization accuracy of 98.98%.
Strategi Kepala Sekolah dalam Memaksimalkan Supervisi melalui Pendidikan berbasis Budaya
Authors: Nur Qorimah Esti , Laksono Wisnu Cahyo 
Published: February 2024

Tujuan penelitian ini adalah untuk mendeskripsikan pendidikan berbasis budaya, strategi implementasi pendidikan berbasis budaya, komponen pembelajaran berbasis budaya, kendala dan solusi dalam implementasi pendidikan berbasis budaya. Metode yang digunakan dalam penelitian ialah literature review berisi tentang gambaran singkat dari suatu topik penelitian dan diorganisasikan secara kronologis serta tematik. Hasil dari penelitian ini adalah : 1) Pendidikan berbasis budaya untuk menanamkan nilai budaya dalam diri seorang anak; 2) Strategi dalam pendidikan berbasis budaya dilakukan melalui pembelajaran berbasis budaya, integrasi pada tema pembelajaran, kegiatan pendukung pembelajaran, budaya sekolah; 3) komponen pembelajaran berbasis budaya terdiri dari substansi (materi) dan kompetensi atau bidang ilmu, kebermaknaan dan proses pembelajaran, penilaian hasil belajar, dan peran budaya; 4) Kendala dalam mengimplementasikannnya, yaitu media ajar kurang, guru sulit untuk menemukan budaya lokal yang terdapat pada lingkungan sekitar sekolah, guru kesulitan dalam mengintegrasikan budaya dengan materi yang akan diajarkan, guru belum kreatif untuk mengembangkan media pembelajaran atau bahan ajar.
Tingkat Kesulitan Pembelajaran Pendidikan Jasmani: Studi Cross Sectional Pada Siswa SMPN 2 Pomala
Authors: Haris Iyan , Yulianto Ari Gana , Ernawati Ernawati , Akbar Muhammad 
Published: February 2024

Penelitian ini bertujuan untuk mengetahui seberapa tinggi tingkat kesulitan belajar siswa di SMPN 2 Pomala dalam belajar pendidikan jasmani. Penelitian ini menggunakan penelitian deskriptif kuantitatif dengan menggunakan metode survei dengan jenis cross-sectional. Populasi dalam penelitian ini adalah siswa SMPN 2 Pomalaa yang memiliki total siswa 140 dari kelas VII sampai kelas IX. Penarikan sampel dilakukan dengan cara Simple rendom sampling (pengundian) Jadi sampel pada penelitian ini berjumlah 30 siswa. Hasil penelitian menunjukan bahwa tingkat kesulitan pembelajaran pendidikan jasmani pada siswa SMPN 2 Pomalaa menunjukan bahwa 2 siswa (6,7%) siswa yang mengalami kesulitan pembelajaran pendidikan jasmani pada kategori sangat rendah, 13 siswa (43,3%) pada kategori rendah, 15 siswa (50,0%) pada kategori sedang, 0 siswa (0,0%) pada kategori tinggi, dan 0 siswa (0,0%) pada kategori sangat tinggi. Hasil penelitian ini diharapkan dapat menjadi dasar untuk memilih model pembelajaran yang dapat mengatasi tingkat kesulitan pembelajaran pendidikan jasmani yang dialami siswa.
Information Compensation Graph Contrastive Learning for Recommendation
Authors: Guo YunLong , Wang ZhenHai , Xu YuHao , Li WeiMin , Wang ZhiRu , Fan Rong 
Published: February 2024

Abstract
Applying graph convolutional neural networks to collaborative filtering is a novel approach pertaining to recommendation systems currently, which has afforded suitable results. However, certain problems still limit the performance of graph collaborative filtering, such as the data uniformity problem. In other words, the quality of embedding the expression of different data after multiple convolutions is reduced, leading to the decline of push model performance. In this paper, we propose self-supervised contrastive learning using global information compensation of feature embeddings, which can effectively alleviate the problem of data uniformity and improve model robustness. Simultaneously, we also propose a graph convolution method using local cooperative propagation to improve the performance of the recommendation model. This embedding calculation method for local cooperative propagation can maximize the influence of low-layer embedding on high-layer embedding, thereby improving the high-layer embedding uniformity. Experiments show that compared with the baseline, our model exhibits significantly improved performance on the three public datasets. Partially on the ML-1M dataset, the proposed ICCL exhibits a performance improvement of 7.96%, proving that our method is valid and explainable.
Enantioselective Alkyl-Alkyl Coupling by Ni-Catalyzed Asymmetric Cross-Hydrodimerization of Alkenes
Authors: Shu Wei , Yang Peng-Fei , Zhao Han-Tong , Chen Xiao-Yi 
Published: February 2024

Abstract

Saturated tertiary stereogenic carbon centers consist of much of the frameworks of small molecules and organic materials. Transition-metal-catalyzed asymmetric alkyl-alkyl bond-formation processes represent contemporary techniques for the straightforward and efficient construction of saturated tertiary stereogenic carbon centers. However, reaction modes for asymmetric alkyl-alkyl bonds (Csp3-Csp3) formation between sp3 hybridized carbons are extremely limited and highly desirable. Herein, an unprecedented mode for asymmetric alkyl-alkyl bond-forming process enabled by Ni-catalyzed asymmetric alkyl-alkyl cross-coupling from alkenes has been developed to construct tertiary stereogenic carbon centers. Ni-catalyzed asymmtric cross-hydrodimerization of N-acyl enamines and unactivated alkenes to enables head-to-tail regioselectivity and exellent levels of chemo- and enantioselectivity, providing a new reaction mode to achieve asymmetric alkyl-alkyl bond-forming event. Notably, the reaction proceeds in the presence of both reducing and oxidizing reagents, rendering alkenes as the sole precursors to forge enantioselective alkyl-alkyl bonds. The exclusive head-to-tail cross-hydrodimerization of distinct alkenes, opening a new avenue to access saturated tertiary stereogenic carbon centers from alkenes.
A Seamless Auxetic Substrate with a Negative Poisson’s Ratio of -1
Authors: Bae Byeong-Soo , Lee Yung , Jang Bongkyun , Song Hyunggwi , Kim Sumin , Kwon Yong Won , Kang Hyun Seok , Kim Min Seong , Park Inkyu , Kim Taek-Soo , Jang Junho , Kim Jae-Hyun , Park Jang-Ung 
Published: February 2024

Abstract

Auxetic metamaterials are a unique class of materials or structures with a negative Poisson’s ratio and a wide array of functionalities.1-3 However, their inherent porosity presents challenges in practical applications.4,5 Filling the inherent perforations while preserving their unique auxeticity is difficult because it demands the seamless integration of components that have unusual and extreme mechanical characteristics.6,7 Here we introduce an unprecedented seamless auxetic substrate film capable of achieving a negative Poisson’s ratio of -1, the theoretical limit of isotropic materials.8,9 This breakthrough was realized by incorporating a highly rigid auxetic structure reinforced by glass-fabric, with surface-flattening soft elastomers. We effectively optimized the mechanical properties of these components by systematic experimental and theoretical investigations into the effects of relative differences in the moduli of the constituents. Using the developed auxetic film we demonstrated an image distortion-free display having 25 PPI resolution of micro-LEDs that is capable of 25% stretching without performance degradation.