bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contradictions to decent African jobs under energy transition-related extractivism: the case of graphite mining in Mozambique
Authors: Namaganda Emilinah 
Published: December 2023

ABSTRACTThe power of African labour to bargain for better terms of employment is an important precondition to ensuring decent jobs under energy transition-related resource (ETR) extraction and the global renewable energy sector more broadly. Through the lens of graphite mining communities in Cabo Delgado Province in Mozambique, this article examines the socio-economic contradictions constraining the power of residents to negotiate decent jobs from ETR projects in Cabo Delgado and other regions of the country. Six principal but intertwined contradictions are identified, including regional antipathies and limited livelihood alternatives, engaging energy transition discussions in Mozambique on the issues unfolding at the local level which inhibit workers from negotiating decent jobs. A micro-level perspective to examining challenges to decent African jobs enables critical reflection on the local aptness of climate change policies, such as the energy transition, which are predominantly discussed at the global, regional and national levels.
State-of-the-art with the prospects of cobalt-based metal-organic frameworks for solar cell applications
Authors: Chuhadiya Sakshi , Sharma Ritika , Beniwal S K , Kamlesh  , Dhaka M S 
Published: December 2023

Abstract
The characteristics of metal–organic framework (MOF) composites make them the most significant materials for energy conversion applications. MOFs are hybrid molecular frameworks synthesized using metal ions like Copper, Cobalt, Zinc, Nickel, etc and organic ligands such as BTC, NDC, etc. To meet and fulfill futuristic energy demands and needs, it is feasible to expand cost-effective energy conversion solar cell devices using MOF materials, therefore in the present work, the Cobalt-based MOFs (Co-MOF) are synthesized by coordinating Cobalt nitrate and 1,3,5 Benzene tricarboxylic acid (BTC or Trimesic acid) ligand using the Solvothermal method. To study the physiochemical properties of synthesized Co-BTC MOFs, these have gone through a variety of characterization processes where the structural exploration unveils that the intensity of the dominant peak obtained at 18.7° gradually decreases with a decrease in the concentration of trimesic acid ligand. First and second weight losses, corresponding to release of the solvent molecules and breakdown of the frameworks, respectively, were detected by thermogravimetric analysis (TGA) measurements. In the FTIR spectra, metal-oxide, modified benzene, carboxylic, and hydroxyl groups with different modes of vibrations are observed. Analysis of surface morphology demonstrated creation of rod-like geometry to the synthesized materials, whereas elemental studies inveterate effective formation of the Co-BTC MOFs. Additionally, the optimized Co-BTC MOF is applied as a potential interfacial layer in solar cells and the outcome implies that the device designed with 10 Co-BTC LBL cycle evolutions provided relatively desirable solar cell performance parameters. The present findings recommended that material progression is necessary to develop cost-effective and high-performance MOF-based solar cell devices.
Soliton molecules, Y-type soliton and complex multiple soliton solutions to the extended (3+1)-dimensional Jimbo-Miwa equation
Authors: Wang Kang-Jia 
Published: December 2023

Abstract
The central purpose of this paper is extracting some novel and interesting soliton solutions of the extended (3+1)-dimensional Jimbo-Miwa equation(JME) which acts as an extension of the classic (3+1)-dimensional JME for the plasma and optics. First, we study the N-soltion solutions that is developed by the Hirota bilinear method (HBM). Then, the soliton molecules and Y-type soliton solutions are constructed via imposing the novel resonance conditions to the N-soltion solutions. In addition, we also explore the complex multiple soliton solutions via the HBM. The dynamic properties of the N-soltion, soliton molecules, Y-type soliton as well as the complex multiple soliton solutions are presented graphically. The developed soliton solutions of this research are all new and can enable us apprehend the nonlinear dynamic behaviors of the extended (3+1)-dimensional JME better.
Comparative study of recursive least squares with variable forgetting factor applied in AC loss measurement
Authors: Long Feiyang , Xu Ying , Li Xin , Ren Li , Shi Jing , Tang Yuejin , Guo Fang , Xia Yajun 
Published: December 2023

Abstract
AC loss has significant impact on the design and safe operation of superconducting power equipment. While there have been numerous simulation studies on AC loss, experimental measurement has proven challenging due to its relatively small magnitude compared to reactive power. In our previous work, a method based on fixed forgetting factor recursive least squares for measuring instantaneous AC loss is proposed. However, its applicability is limited due to the varying characteristics of each parameter in superconductors. This paper introduces four recursive least squares with variable forgetting factor algorithms and measures AC loss in ten different superconducting coils. The accuracy of these algorithms is analysed and compared using the integral method as benchmark. The results demonstrate that the recursive least squares with leverage-based multiple adaptive forgetting factors offers the widest range for AC loss measurements.
Capacity prediction of Lithium-ion batteries based on adaptive sliding window pooling extreme learning machine algorithm
Authors: Han Caiyun , Yuan Huimei 
Published: December 2023

Abstract
Considering the safety and reliability, it is especially important to accurately predict the capacity decline trend of lithium-ion batteries. In this paper, a simple and easy-to-operate singular value decomposition technique is used to extract the health indicators (HIs) that are correlated with the capacity from the measurable parameters of battery, and then the HIs that have a high Pearson correlation coefficient with the capacity are selected for predicting the battery capacity. Aiming at the problems of low prediction accuracy and random dispersion of traditional extreme learning machine (ELM), this paper proposes an adaptive sliding window pooling extreme learning machine (ASW-PELM) algorithm. The algorithm first adaptively adjusts the window length according to the fluctuation of local data, and then dynamically traverses the data with the sliding window for data enhancement, and this adaptive sliding window mechanism provides effective data for the model prediction stage. Then it combines the pooling operation and the ELM to replace the random factor between the input layer and the hidden layer, which effectively solves the problem of random dispersion in the original learning model. The results of lithium battery capacity prediction under two sets of different experimental conditions show that the method has the highest prediction accuracy compared with other generalized algorithms.
Structural, electronic and optical properties of synthesized schiff base compound-validation with a computational method
Authors: Kumar Ch Ravi Shankar , Prasanti M , Jha Anjali , Kumar B Rajesh 
Published: December 2023

Abstract
Organic molecules have a profound impact on present-day technologies due to their structure, molecular interactions, ease of modification, and synthesis. The motivation of the present study is to synthesize a dielectric material at room temperature to accurately determine the optical properties the refractive index and dielectric constant and validate it using a computational method. Organic Schiff base compounds are synthesized in equimolar ratios with the host molecule Biphenyl-4-carboxaldehyde and guest molecules a family of distinct anilines using ultrasonication method. The advantages of this method over other conventional methods are a shorter reaction time, lower operating temperature, and easy work up with fewer amounts of solvents. Molecular aspects of synthesized Schiff bases were established by spectroscopic techniques i.e., IR, proton NMR and powdered x-ray diffraction methods showed that these results are consistent with the expected structure. Optical properties the refractive index and dielectric constant were recorded with a spectroscopic ellipsometer. Studies of computational methods provided optimized molecular structures with minimum energy with wavenumbers in agreement with recorded spectra. Quantum mechanical descriptors provide information on electronic and optical properties and help to visualize the corresponding changes in electron density using the Gaussian 16 package. The results of spectroscopic studies are in agreement with computed studies indicating that synthesized Schiff bases are active dielectric materials with major role of nitro compounds best suitable for optical and electronic properties with increased dielectric constant, refractive index and reduced energy.
Uncertain M-fractional differential problems: existence, uniqueness, and approximations using Hilbert reproducing technique provisioner with the case application: series resistor-inductor circuit
Authors: Maayah Banan , Arqub Omar Abu 
Published: December 2023

Abstract
In this article, the principle of characterization is proposed as a new tool for solving uncertain M-fractional differential problems under firmly generalized differentiability. The study demonstrates the solvability of such issues by presenting theoretical implications on the existence and uniqueness of two uncertain M-solutions. Additionally, the study provides quantitative solutions in a novel uncertain framework using two Hilbert spaces that are combined through the kernel-based Gram-Schmidt orthogonalization technique. The proposed uncertain problems and algorithms are examined, with a focus on analyzing the solution collection, assessing convergence, and evaluating errors. The debatable Hilbert approach can solve numerous M-fractional differential problems under uncertainty, and the numerical results demonstrate the accuracy and effectiveness of the algorithm. Based on the figures, tables, and quantitative analysis, our work significantly enhances mathematical tools for solving complex M-fractional differential problems under uncertainty. By utilizing the numerical pseudocode; this advancement has the potential to make an impact on various scientific and engineering fields. The final section presents numerical notes, along with recommendations for future research directions. Additionally, an evaluation of the study’s findings is provided based on the conducted analysis.
Hamilton energy of a complex chaotic system and offset boosting
Authors: Gao Xiaohong 
Published: December 2023

Abstract
The complex differential system can be obtained by introducing complex variable in the real differential system. Complex variables can be decomposed into real component and imaginary component, which makes the complex differential systems have more complex dynamic behaviors. Complex chaotic system is used in secure communications to increase the security of cryptographic systems. In this study, we designed a complex differential system by incorporating a complex variable into a 3D differential system. Dynamics of this complex differential system are investigated by applying typical nonlinear analysis tools. Furthermore, Hamilton energy function for complex differential system is obtained based on Helmholtz’s theorem. The values of Hamilton energy with different oscillations of complex differential system are calculated. In addition, offset boosting control for the complex chaotic signal is realized by adding a constant to variable of complex system. Simulation shows that the position of the chaotic attractor in phase space can be flexibly shifted by applying the offset parameter.
Impact of viscothermal loss on modulation instability and rogue waves in left-handed nonlinear diffractive acoustic transmission line metamaterials
Authors: Joseph Mora , David Vroumsia , Justin Mibaile , Sindanne Azakine Sylvere , Betchewe Gambo , Yamigno Serge Doka 
Published: December 2023

Abstract
In this study, the transmission line approach is used to describe the studied acoustic metamaterial model. Through Kirchoff’s pressure and volume-velocity laws and using multiple scales method, nonlinear coupled Schrödinger equations are obtained. Then, the amplitude disturbance method is applied to these equations to obtain and plot the modulational instability gain curves. Analytically, the impact of viscothermal loss on the modulational instability gain is studied. The similarity technique is used to derive integrable Manakov’s equations. First and second-order rational rogue wavelike solutions of coupled nonlinear Schrödinger are deduced. The results indicate that the modulational instability gain and Rogue wave intensities depend on the viscothermal parameter. This parameter can be considered in the design of nonlinear acoustic metamaterials to minimize the damage caused by the dynamics of freak waves.
Improved solar cell efficiency of titanium dioxide on porous silicon using pulsed laser deposition at different laser wavelengths
Authors: Fakhri Makram A , Salim Evan T , Mohammed Rami S , Azzahrani Ahmad S , Ibrahim Raed Khalid , Gopinath Subash C B , Salim Zaid T 
Published: December 2023

Abstract
In this study, a Q-switched Nd:YAG laser with specific parameters, including a pulse repetition rate of 6 Hz, a pulse duration of 10 nm, a wavelength of 532 nm, and a laser fluence of 237.47 J cm−12, was employed to fabricate highly crystalline TiO2 nano-films. These nano-films exhibited a narrow energy band gap of 3.24 eV and showcased favorable surface morphology, characterized by a roughness of 2.38 nm. A solar cell device was produced by creating porous silicon (PSi) and applying titanium dioxide films onto the PSi, achieving a notable conversion efficiency of 8.733%. To investigate the impact of different parameters on the resulting TiO2 nano-films, a range of laser fluences (ranging from 131.93 to 263.85 J cm−12) and three distinct laser wavelengths (1064 nm, 532 nm, and 355 nm) were employed during the pulsed laser deposition (PLD) process. These experiments aimed to grow TiO2 films on both quartz and silicon (Si) substrates.
Pseudo-online framework for BCI evaluation: a MOABB perspective using various MI and SSVEP datasets
Authors: Carrara Igor , Papadopoulo Theodore 
Published: December 2023

Abstract

Objective. BCI (Brain–Computer Interfaces) operate in three modes: online, offline, and pseudo-online. In online mode, real-time EEG data is constantly analyzed. In offline mode, the signal is acquired and processed afterwards. The pseudo-online mode processes collected data as if they were received in real-time. The main difference is that the offline mode often analyzes the whole data, while the online and pseudo-online modes only analyze data in short time windows. Offline processing tends to be more accurate, while online analysis is better for therapeutic applications. Pseudo-online implementation approximates online processing without real-time constraints. Many BCI studies being offline introduce biases compared to real-life scenarios, impacting classification algorithm performance. Approach. The objective of this research paper is therefore to extend the current MOABB framework, operating in offline mode, so as to allow a comparison of different algorithms in a pseudo-online setting with the use of a technology based on overlapping sliding windows. To do this will require the introduction of a idle state event in the dataset that takes into account all different possibilities that are not task thinking. To validate the performance of the algorithms we will use the normalized Matthews correlation coefficient and the information transfer rate. Main results. We analyzed the state-of-the-art algorithms of the last 15 years over several motor imagery and steady state visually evoked potential multi-subjects datasets, showing the differences between the two approaches from a statistical point of view. Significance. The ability to analyze the performance of different algorithms in offline and pseudo-online modes will allow the BCI community to obtain more accurate and comprehensive reports regarding the performance of classification algorithms.
Application of the grade selection of X-ray events using machine learning for a CubeSat mission
Authors: Shen H.C. , Sakamoto T. , Serino M. , Ogino N. , Arimoto M. 
Published: December 2023

Abstract
X-ray observation covering a wide field of view with high sensitivity is essential in
searching for an electromagnetic counterpart of gravitational wave events. A lobster-eye optics
(LEO) and a large area CMOS sensor are effective instruments to achieve this goal. Furthermore,
thanks to the light weight of LEO, it can be installed on a small platform such as a CubeSat.
However, the real-time identification of X-ray events is challenging with restricted resources on
space. Therefore, we trained a image recognition network utilizing one of the machine learning
models of convolutional neural network (CNN). Then, we use this network to identify X-ray events
in the image taken from a CMOS sensor. Moreover, we use a Sony single-board computer, Spresense,
that provides ultra-low power consumption and supports machine learning libraries for the process.
This paper introduces our machine learning-based X-ray event selection process that is targeted
for use on a CubeSat.
Heterogeneous effects of weather extremes on different dimensions of poverty in Kyrgyzstan
Authors: Kimsanova Barchynai , Umirbekov Atabek , Herzfeld Thomas , Müller Daniel 
Published: December 2023

Abstract
Weather extremes become more frequent and intense with climate change, but how weather extremes impact household wealth in the Global South remains elusive in many regions. We combined nationally representative quarterly household panel data with climate data to evaluate the impact of weather extremes on household poverty in Kyrgyzstan between 2013 and 2020. We evaluated multiple dimensions of poverty by quantifying changes in nutrition, education, health, and living standards. We used a linear quantile mixed model to relate the poverty dimensions with four salient weather extremes: cold winters, hot summers, excessive rains, and dry spells. Our findings show that all weather extremes harmed household wealth but with substantial spatial variation. Cold winters were the most detrimental, with negative consequences that continued into the subsequent year. Poor households suffered disproportionally more from extremes than rich ones. Our results underscore the need to initiate place-based adaptation options to cushion the adverse effects of extreme weather events on household wealth.
Plastic Surgery Tourism: Complications, Costs, and Unnecessary Spending?
Authors: Hery Danielle , Schwarte Brandon , Patel Krishna , Elliott John O , Vasko Susan 
Published: December 2023

Abstract

Background
The liability of plastic surgery tourism in patient health and postoperative resource allocation is significant. Procedures completed within the context of medical tourism often lack rigorous quality assurance and provide limited preoperative evaluation or postoperative care. Not only does this jeopardize the patient's well-being, but it also increases the financial burden and redirects invaluable resources domestically through often unnecessary diagnostic tests and hospitalizations.

Objectives
This manuscript will examine the complications and associated costs following plastic surgery tourism and highlight unnecessary expenses for patients with outpatient complications.

Methods
A retrospective review was conducted of all patients 18 years or older who underwent destination surgery and were seen within 1 year postoperatively in consultation with plastic surgery at our health system between January 11, 2015 and January 7, 2022. Patient admissions were reviewed and deemed necessary or unnecessary after review by 2 physicians.

Results
The inclusion criteria were met by 41 patients, of whom hospitalization was deemed necessary in 28 patients vs unnecessary in 13 patients. The most common procedures included abdominoplasty, liposuction, breast augmentation, and “Brazilian butt lift.” The most common complications were seroma and infection. Patients deemed to have a necessary admission often required at least 1 operation, were more likely to need intravenous antibiotics, were less likely to have the diagnosis of “pain,” necessitated a longer hospitalization, and incurred a higher cost. The total financial burden was $523,272 for all 41 patients.

Conclusions
Plastic surgery tourism poses substantial health risks, the morbidities are expensive, and it strains hospital resources.

Level of Evidence: 5
Explainable artificial intelligence for omics data: a systematic mapping study
Authors: Toussaint Philipp A , Leiser Florian , Thiebes Scott , Schlesner Matthias , Brors Benedikt , Sunyaev Ali 
Published: December 2023

Abstract
Researchers increasingly turn to explainable artificial intelligence (XAI) to analyze omics data and gain insights into the underlying biological processes. Yet, given the interdisciplinary nature of the field, many findings have only been shared in their respective research community. An overview of XAI for omics data is needed to highlight promising approaches and help detect common issues. Toward this end, we conducted a systematic mapping study. To identify relevant literature, we queried Scopus, PubMed, Web of Science, BioRxiv, MedRxiv and arXiv. Based on keywording, we developed a coding scheme with 10 facets regarding the studies’ AI methods, explainability methods and omics data. Our mapping study resulted in 405 included papers published between 2010 and 2023. The inspected papers analyze DNA-based (mostly genomic), transcriptomic, proteomic or metabolomic data by means of neural networks, tree-based methods, statistical methods and further AI methods. The preferred post-hoc explainability methods are feature relevance (n = 166) and visual explanation (n = 52), while papers using interpretable approaches often resort to the use of transparent models (n = 83) or architecture modifications (n = 72). With many research gaps still apparent for XAI for omics data, we deduced eight research directions and discuss their potential for the field. We also provide exemplary research questions for each direction. Many problems with the adoption of XAI for omics data in clinical practice are yet to be resolved. This systematic mapping study outlines extant research on the topic and provides research directions for researchers and practitioners.