bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting the Range of Possible Human Hand Movement in Consumer Electronics Disassembly Using Machine Learning
Authors: Liao Hao-Yu , Chen Yuhao , Hu Boyi , Liang Xiao , Behdad Sara 
Published: September 2023

Abstract
Robotic technology can benefit disassembly operations by reducing human operators’ workload and assisting them with handling hazardous materials. Safety consideration and predicting human movement is a priority in human-robot close collaboration. The point-by-point forecasting of human hand motion which forecasts one point at each time does not provide enough information on human movement due to errors between the actual movement and predicted value. This study provides a range of possible hand movements to enhance safety. It applies three machine learning techniques including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bayesian Neural Network (BNN) combined with Bagging and Monte Carlo Dropout (MCD), namely LSTM-Bagging, GRU-Bagging, and BNN-MCD to predict the possible movement range. The study uses an Inertial Measurement Units (IMU) dataset collected from the disassembly of desktop computers to show the application of the proposed method. The findings reveal that BNN-MCD outperforms other models in forecasting the range of possible hand movement.
Online Cost-Effective Classification of Mixed Tool and Material Conditions in Ultrasonic Metal Welding: Towards Integrated Monitoring and Control
Authors: Lu Kuan-Chieh , Meng Yuquan , Dong Zhiqiao , Shao Chenhui 
Published: September 2023

Abstract
Ultrasonic metal welding (UMW) is widely used in industrial applications such as electric vehicle battery manufacturing and automotive body assembly. The joint quality of UMW is sensitive to a variety of undesired yet inevitable process disturbances such as tool condition and material surface condition. Online monitoring and control capabilities are critically needed to quickly detect process anomalies and adaptively adjust process parameters, thus ensuring satisfactory joint quality and reducing process variability. While existing research has developed online quality monitoring methods for UMW, the cost-effectiveness of hardware (sensors, data acquisition equipment, and edge-computing devices) and software (computational efficiency) in a monitoring system has not been investigated systematically. The cost-effectiveness of monitoring also decides the window during which control actions can be executed, thus ultimately influencing the joint quality. This paper presents a systematic study on three factors related to cost-effectiveness: (1) sensor selection, (2) sampling rate of data acquisition, and (3) signal fraction. A method based on discrete wavelet transformation (DWT) is used for automatic feature extraction due to its effectiveness in extracting both time-domain and frequency-domain information with varying signal lengths. We develop a multi-layer perceptron (MLP) classifier to process DWT-generated features and recognize two types of welding disturbances including tool condition and material surface condition. Case studies demonstrate that combining a suitable signal fraction with a subset of sensors leads to comparable performance to using all sensors at full length. Moreover, the interaction between the sampling rate and the signal fraction is investigated. Results confirm the feasibility of building an accurate monitoring system with limited sampling rate and signal fraction, which increases the window for real-time control.
Printability Prediction in Projection Two-Photon Lithography via Machine Learning Based Surrogate Modeling of Photopolymerization
Authors: Pingali Rushil , Saha Sourabh K. 
Published: September 2023

Abstract
The two-photon lithography (TPL) direct laser writing process enables the fabrication of complex three-dimensional features with sub-micrometer resolution. While traditional TPL techniques have suffered from low throughput due to their serial writing scheme, the process has been recently parallelized through the development of the projection two photon lithography (P-TPL) process that allows printing of entire layers at once. In this work, we use machine learning-based surrogate modeling to predict the outcomes of P-TPL to &gt; 97% of the accuracy of a physics-based reaction-diffusion finite element simulation. Training a classification neural network on data points generated from physics-based simulations allows for computationally efficient and accurate prediction of whether a set of printing conditions will result in precise and controllable polymerization and the desired printing, as opposed to no printing or runaway polymerization. We interrogate this surrogate model to investigate the parameter regimes that are promising for successful printing. We predict combinations of rate constants necessary to print for a given set of material properties, thereby generating the first printability map for the P-TPL process and allowing informed selection of photoresists and printing parameters in the future.
Effect of Multi-Axial Forging on Mechanical Properties and Microstructures of AA7075/TaC Composites
Authors: Khalkho John Samson , Karunakar D. Benny 
Published: September 2023

Abstract
The objective of the current work is to develop a AA7075 reinforced Tantalum Carbide (1, 3, 5, and 7 wt%) composite through stir casting. The secondary process such as Multi-axial forging (MAF) followed by ageing was performed on AA7075/5TaC(S-4) composite to enhance the strength and ductility of composite. The evolution of microstructures were examined by Optical microscope (OM) and Field emission scanning electron microscopy (FESEM) and the MAF process was analyzed by Electron back scattered diffraction (EBSD). The microstructure characterization reveals that refinement of grains take place with the addition of TaC due to the pinning effect. The microstructure of the MAF shows suppression of dynamic recovery and generation of dislocation density because of strain energy effect at room temperature. The mechanical properties were measured by Vickers hardness and universal tensile testing machine and obtained as the highest for 5 wt % TaC which is 142 Hv, 211 YS, and 254 UTS. MAF specimen shows an improvement in mechanical properties and percentage elongation compared to properties obtained in S-4 composite specimen. The highest UTS, YS, and % Elongation of S-4 specimen was achieved with MAF+aged when the cumulative strain was up to 4.8. The enhancement in hardness and tensile strength of the developed composite and MAF specimen were discussed with various strengthening mechanisms.
Transfer Learning for Predictive Quality in Laser-Induced Plasma Micro-Machining
Authors: Chen Mengfei , Malhotra Rajiv , Guo Weihong “Grace” 
Published: September 2023

Abstract
In laser-induced plasma micro-machining (LIPMM), a focused, ultrashort pulsed laser beam creates a highly localized plasma zone within a transparent liquid dielectric. When the beam intensity is greater than the breakdown threshold in the dielectric media, plasma is formed which is then used to ablate the workpiece. This paper aims to facilitate in-situ process monitoring and quality prediction for LIPMM by developing a deep learning model to (1) understand the relationship between acoustic emission data and quality of micro-machining with LIPMM, (2) transfer such understanding across different process parameters, and (3) predict quality accurately by fine-tuning models with a smaller dataset. Experiments and results show that the relationship learned from one process parameter can be transferred to other parameters, requiring lesser data and lesser computational time for training the model. We investigate the feasibility of transfer learning and compare the performance of various transfer learning models: different input features, different CNN structures, and the same structure with different fine-tuned layers. The findings provide insights into how to design effective transfer learning models for manufacturing applications.
Simulation and Experiment Analysis of Driveshaft
Authors: Li Jiahao , Liu Yao , Zhou Yang , Wang Youzhe , Guo Zhanling , Shen Bin 
Published: September 2023

Abstract
Driveshaft is a small spring coil (usually less than 1mm in diameter), made by several stainless-steel wire filaments, which transmits force and motion to the body through existing micro channels (such as arteries, veins, and gastrointestinal tract). The performance of the driveshaft determines the efficiency, stability, accuracy of force and motion transitions, the ability to pass through tortuous microchannels, and the damage to healthy tissues. In order to determine the influence of fabrication parameters (filament, wire diameter, outer diameter) on the mechanical properties (such as bending stiffness and natural frequency) of the driveshaft, a simulation was established in ABAQUS to calculate the deformation displacement under 0.0098N and first order natural frequency. The bending stiffness is calculated further. The results show that the bending stiffness and the first natural frequency of the driveshaft increase with the increase of the filament number and wire diameter. When the outer diameter of driveshaft increases, the bending stiffness increases, while the first order natural frequency decreases. In order to verify the simulation model, deformation displacement was measured in experiments. This study provides an idea for the design and selection of the driveshaft in the intervention process.
Determination of Body Composition in Community-Dwelling Older Adults With and Without Sarcopenia Using Data From Practical Measures
Authors: Amatachaya Sugalya , Chokphukiao Pakwipa , Poncumhak Puttipong , Intaruk Roongnapa , Thaweewannakij Thiwabhorn , Amatachaya Pipatana 
Published: September 2023

Adequate body composition is essential for health, function, and independence in older adults. However, standard body composition assessments require complex and costly modalities, limiting their use for early detection of body composition changes and periodic follow-up. This study explored the ability of three practical measures—handgrip strength, five times sit-to-stand test, and upper limb loading during seated push-up test (ULL-SPUT)—to determine body composition in 109 older adults with and without sarcopenia. Participants (average age 76 years) were cross-sectionally measured for outcomes of the study. The ULL-SPUT and handgrip strength, but not the five times sit-to-stand test, significantly correlated with body composition (rs, r = .297–.827, p < .01). The ULL-SPUT, in combination with demographic data, could determine body composition up to 82%. Therefore, the ULL-SPUT may be a practical preliminary measure to identify older adults for whom standard body composition assessments and follow-up would prove timely and beneficial.
Impact of antibiotic pharmacokinetics in urine on recurrent bacteriuria following treatment of complicated urinary tract infections
Authors: Melnick David , Talley Angela K. , Gupta Vipul K. , Critchley Ian A. , Eckburg Paul B. , Hamed Kamal A. , Bhatt Nivedita , Moore Gary , Austin Daren , Rubino Christopher M. , Bhavnani Sujata M. , Ambrose Paul G. 
Published: September 2023

ABSTRACT
The clinical relevance of bacteriuria following antibiotic treatment of complicated urinary tract infections in clinical trials remains controversial. We evaluated the impact of urine pharmacokinetics on the timing of recurrent bacteriuria in a recently completed trial that compared oral tebipenem pivoxil hydrobromide to intravenous ertapenem. The urinary clearance and urine dwell time of ertapenem were prolonged relative to tebipenem and were associated with a temporal difference in the repopulation of bladder urine with bacteria following treatment, potentially confounding the assessment of efficacy.
The REEP5/TRAM1 complex binds SARS-CoV-2 NSP3 and promotes virus replication
Authors: Li Jie , Gui Qi , Liang Feng-Xia , Sall Joseph , Zhang Qingyue , Duan Yatong , Dhabaria Avantika , Askenazi Manor , Ueberheide Beatrix , Stapleford Kenneth A. , Pagano Michele 
Published: September 2023

ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), like other coronaviruses, replicates their genome in virus-induced cytosolic membrane-bound replication organelles (ROs). SARS-CoV-2 promotes the biogenesis of ROs by inducing the rearrangement of endoplasmic reticulum (ER) membranes. NSP3, NSP4, and NSP6 are transmembrane viral non-structural proteins (NSPs) and essential players in the formation of ROs. To understand how these three NSPs work synergistically with host-binding proteins, we performed affinity purifications followed by mass spectrometry analyses to study the host-viral protein-protein interactome of NSP3, NSP4, and NSP6 expressed individually and in combination. Through this analysis, we identified two host transmembrane proteins, REEP5 and TRAM1, as critical interacting partners of NSP3 that localize at the membrane of the RO. REEP5 interacts with TRAM1 endogenously and binds NSP3 during SARS-CoV-2 infection. REEP5 knockout reduces ER membrane rearrangements and inhibits SARS-CoV-2 replication. Collectively, our study shows that the host REEP5/TRAM1 complex binds NSP3, promoting RO biogenesis and viral replication.

IMPORTANCE
Generation of virus-host protein–protein interactions (PPIs) maps may provide clues to uncover SARS-CoV-2-hijacked cellular processes. However, these PPIs maps were created by expressing each viral protein singularly, which does not reflect the life situation in which certain viral proteins synergistically interact with host proteins. Our results reveal the host-viral protein-protein interactome of SARS-CoV-2 NSP3, NSP4, and NSP6 expressed individually or in combination. Furthermore, REEP5/TRAM1 complex interacts with NSP3 at ROs and promotes viral replication. The significance of our research is identifying virus-host interactions that may be targeted for therapeutic intervention.
Division of labor within psyllids: metagenomics reveals an ancient dual endosymbiosis with metabolic complementarity in the genus
Cacopsylla
Authors: Dittmer Jessica , Corretto Erika , Štarhová Serbina Liliya , Michalik Anna , Nováková Eva , Schuler Hannes 
Published: September 2023

ABSTRACT

Hemipteran insects are well-known for their ancient associations with beneficial bacterial endosymbionts, particularly nutritional symbionts that provide the host with essential nutrients such as amino acids or vitamins lacking in the host’s diet. Therefore, these primary endosymbionts enable the exploitation of nutrient-poor food sources such as plant sap or vertebrate blood. In turn, the strictly host-associated lifestyle strongly impacts the genome evolution of the endosymbionts, resulting in small and degraded genomes. Over time, even the essential nutritional functions can be compromised, leading to the complementation or replacement of an ancient endosymbiont by another, more functionally versatile bacterium. Herein, we provide evidence for a dual primary endosymbiosis in several psyllid species. Using metagenome sequencing, we produced the complete genome sequences of both the primary endosymbiont “
Candidatus
Carsonella ruddii” and an as yet uncharacterized Enterobacteriaceae bacterium from four species of the genus
Cacopsylla
. The latter represents a new psyllid-associated endosymbiont clade for which we propose the name “
Candidatus
Psyllophila symbiotica.” Fluorescent
in situ
hybridization confirmed the co-localization of both endosymbionts in the bacteriome. The metabolic repertoire of
Psyllophila
is highly conserved across host species and complements the tryptophan biosynthesis pathway that is incomplete in the co-occurring
Carsonella
. Unlike co-primary endosymbionts in other insects, the genome of
Psyllophila
is almost as small as the one of
Carsonella
, indicating an ancient co-obligate endosymbiosis rather than a recent association to rescue a degrading primary endosymbiont.

IMPORTANCE

Heritable beneficial bacterial endosymbionts have been crucial for the evolutionary success of numerous insects by enabling the exploitation of nutritionally limited food sources. Herein, we describe a previously unknown dual endosymbiosis in the psyllid genus
Cacopsylla
, consisting of the primary endosymbiont “
Candidatus
Carsonella ruddii” and a co-occurring Enterobacteriaceae bacterium for which we propose the name “
Candidatus
Psyllophila symbiotica.” Its localization within the bacteriome and its small genome size confirm that
Psyllophila
is a co-primary endosymbiont widespread within the genus
Cacopsylla
. Despite its highly eroded genome,
Psyllophila
perfectly complements the tryptophan biosynthesis pathway that is incomplete in the co-occurring
Carsonella
. Moreover, the genome of
Psyllophila
is almost as small as
Carsonella
’s, suggesting an ancient dual endosymbiosis that has now reached a precarious stage where any additional gene loss would make the system collapse. Hence, our results shed light on the dynamic interactions of psyllids and their endosymbionts over evolutionary time.
The MprF homolog LysX synthesizes lysyl-diacylglycerol contributing to antibiotic resistance and virulence
Authors: Gill Cameron P. , Phan Christopher , Platt Vivien , Worrell Danielle , Andl Thomas , Roy Hervé 
Published: September 2023

ABSTRACT

Lysyl-diacylglycerol (Lys-DAG) was identified three decades ago in
Mycobacterium phlei
, but the biosynthetic pathway and function of this aminoacylated lipid have since remained uncharacterized. Combining genetic methods, mass spectrometry, and biochemical approaches, we show that the multiple peptide resistance factor (MprF) homolog LysX from
Corynebacterium pseudotuberculosis
and two mycobacterial species is responsible for Lys-DAG synthesis. LysX is conserved in most Actinobacteria and was previously implicated in the synthesis of another modified lipid, lysyl-phosphatidylglycerol (Lys-PG), in
Mycobacterium tuberculosis
. Although we detected low levels of Lys-PG in the membrane of
C. pseudotuberculosis
, our data suggest that Lys-PG is not directly synthesized by LysX and may require an additional downstream pathway, which is as yet undefined. Our results show that LysX in
C. pseudotuberculosis
is a major factor of resistance against a variety of positively charged antibacterial agents, including cationic antimicrobial peptides (e.g., human peptide LL-37 and polymyxin B) and aminoglycosides (e.g., gentamycin and apramycin). Deletion of
lysX
caused an increase in cellular membrane permeability without dissipation of the membrane potential, suggesting that loss of the protein does not result in mechanical damage to the cell membrane. Furthermore,
lysX
-deficient cells exhibited an attenuated virulence phenotype in a
Galleria mellonella
infection model, supporting a role for LysX during infection. Altogether, Lys-DAG represents a novel molecular determinant for antimicrobial resistance and virulence that may be widespread in Actinobacteria and points to a richer landscape than previously realized of lipid components contributing to overall membrane physiology in this important bacterial phylum.

IMPORTANCE

In the past two decades, tRNA-dependent modification of membrane phosphatidylglycerol has been implicated in altering the biochemical properties of the cell surface, thereby enhancing the antimicrobial resistance and virulence of various bacterial pathogens. Here, we show that in several Actinobacteria, the multifunctional protein LysX attaches lysine to diacylglycerol instead of phosphatidylglycerol. We found that lysyl-diacylglycerol (Lys-DAG) confers high levels of resistance against various cationic antimicrobial peptides and aminoglycosides and also enhances virulence. Our data show that Lys-DAG is a lipid commonly found in important actinobacterial pathogens, including
Mycobacterium
and
Corynebacterium
species.
Hospitalisations related to nervous-system diseases in Australia, 1998–2019: a secular trend analysis
Authors: Abuhamdah Sawsan MA , Naser Abdallah Y 
Published: September 2023

ObjectiveThe burden of neurological disease-related disabilities and deaths is one of the most serious issues globally. We aimed to examine the hospitalisation profile related to nervous system diseases in Australia for the duration between 1998 and 2019.DesignA secular trend analysis using a population-based dataset.SettingThis analysis used a population-based study of hospitalised patients in Australia. Hospitalisation data were extracted from the National Hospital Morbidity Database, which collects sets of episode-level information for Australian patients admitted to all private and public hospitals.ParticipantsAll patients who were hospitalised in all private and public hospitalisations.Primary outcome measureHospitalisation rates related to nervous system diseases.ResultsHospitalisation rates increased by 1.04 times (from 650.36 (95% CI 646.73 to 654.00) in 1998 to 1328.90 (95% CI 1324.44 to 1333.35) in 2019 per 100 000 persons, p<0.01). Overnight-stay episodes accounted for 57.0% of the total number of hospitalisations. Rates of the same-day hospitalisation for diseases of the nervous system increased by 2.10-fold (from 219.74 (95% CI 217.63 to 221.86) in 1998 to 680.23 (95% CI 677.03 to 683.43) in 2019 per 100 000 persons). Rates of overnight-stay hospital admission increased by 42.7% (from 430.62 (95% CI 427.66 to 433.58) in 1998 to 614.70 (95% CI 611.66 to 617.75) in 2019 per 100 000 persons). ‘Episodic and paroxysmal disorders’ were the most prevalent reason for hospitalisation, which accounted for 49.0% of the total number of episodes. Female hospitalisation rates increased by 1.13-fold (from 618.23 (95% CI 613.24 to 623.22) in 1998 to 1316.33 (95% CI 1310.07 to 1322.58) in 2019 per 100 000 persons). Male hospitalisation rates increased by 86.4% (from 682.95 (95% CI 677.67 to 688.23) in 1998 to 1273.18 (95% CI 1266.98 to 1279.37) in 2019 per 100 000 persons).ConclusionHospitalisation rates for neurological disorders in Australia are high, potentially owing to the ageing of the population. Males had greater rates of hospitalisation than females.