bluuebunny/crossref_metadata_2025_split huggingface dataset:
Special Issue on the Latest Machine Tool and Manufacturing Technologies
Authors: Yoshioka Hayato 
Published: September 2023

The social demands for manufacturing systems are constantly changing with the times. In recent years, environmental and social issues have been complicating these demands. For example, all industrial sectors need to consider environmentally responsible ways to achieve sustainable development goals in a time of paradigm shifts. The demands in the manufacturing field include high productivity, high quality, low energy consumption, and help for aging operators. To meet these various demands for manufacturing systems, we must create innovative manufacturing technologies to realize advanced production systems.
This special issue focuses on state-of-the-art machine tools and manufacturing technologies to accelerate production engineering innovation. This issue consists of eleven research papers covering the following fields.
- Advanced structure and drive systems in machine tools
- Industrial robot applications
- Advanced cutting technologies
- Evaluation and calibration technologies of motion error
- Surface finishing technologies
- Grinding of hard and brittle materials
All of these research contributions were presented at IMEC2022, a joint event with JIMTOF2022, held in Tokyo, Japan in 2022.
I would like to sincerely thank all the authors for their contributions, and I sincerely hope that the papers in this special issue further contribute to the development of our future society.
Analisis Nilai-Nilai Kearifan Lokal dalam Novel Si Dul Anak Jakarta Karya Aman Datuk Madjoindo
Authors: Eliastuti Maguna 
Published: September 2023

Tujuan penelitian ini adalah mendeskripsikan dan menjelaskan nilai kearifan lokal dalam novel Si Dul Anak Jakarta karya Aman Datuk Madjoindo. Penelitian kualitatif deskriptif ini menggunakan pendekatan antropologi sastra. Dalam novel Si Dul Anak Jakarta nilai kearifan lokal dianalisis melalui pendekatan sastra-antropologis. Teknik pengumpulan data yang digunakan adalah membaca, mencatat, dan pengambilan keputusan. Hasil penelitian ini dimaksudkan untuk memberikan analisis tentang nilai kearifan lokal dalam novel Si Dul Anak Jakarta karya Aman Datuk Madjoindo. Secara keseluruhan, novel ini mengandung nilai-nilai kearifan lokal, termasuk pendidikan dan budaya.
Universal protocol for the isolation of channel forming membrane proteins with the recombinant expression system of E. coli.
Authors: Piselli Claudio 
Published: September 2023

Abstract
1 Abstract

The heterologous expression, isolation and characterization of pore forming protein is one of the most used strategy for understanding permeability properties of the biological membrane into which they are embedded. Some procedures present in literature are so empirical and long to perform, that the user can easily make mistakes. This protocol will teach you how to quantify and therefore optimize the expression of your favorite protein in E. coli using the BL21Gold(de3)ΔABCF strain. Then with a step-by-step approach, it will tell you how to separate the bacterial compartments according their solubility and then how to extract your protein in its native conformation using detergent. Finally, there is a detailed description on how to improve the purity of your protein via anion exchange chromatography. If you want to study bacterial porins reconstituted in their natural environment, here there is even the description on how to drive them into the outer membrane vesicles where they can be copurified. The protocol is easier and less empirical than the ones of most of the other membrane proteins and represents a solid base for soluble proteins as well (like enzyme or pore forming toxins). Expression time and temperature, concentration of the inducer, nature and concentration of the detergent, incubation time and temperature, purification pH, these are all the parameters that you can troubleshoot according to your results. The expression, extraction and purification will not last longer than a full day each and I have not yet found any protein which could not be isolated thanks to a derivation of this protocol.
Bringing ImPACT Home: Remote versus Traditional Administration for Collegiate Athletes
Authors: Bennett Ryan , Slicer Kayley , Stafford Claire , Cohen Maya 
Published: September 2023

Abstract

Background
When COVID-19 shut down our once-perceived “normal” societal function, university athletics were forced to change how they conducted concussion baseline screening for their student-athletes. The Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) is a prominent assessment tool used amongst university athletic departments for identifying cognitive baseline functioning of collegiate athletes. The current study aimed to evaluate environmental and supervisory effects of neurocognitive baseline performance and overall symptom reports among student-athletes who took the ImPACT baseline assessment in a clinical setting or a remote environment.
Results
The four univariate ANCOVAs for Verbal Memory (p = 0.787), Visual Memory (p = 0.917), Visual Motor Speed (p = 0.261), and Impulse Control (p = 0.783) were not significantly different between groups. Additionally, the two Quade ANCOVAs for Reaction Time (p = 0.815) and Total Symptom Score (p = 0.886) were not significantly different.
Conclusion
Preliminary findings provide evidence and support that collegiate athletes can complete their baseline ImPACT in an unsupervised remote location without detriment to their performance.
Prevalence of Sarcopenia in Insulin Treated Older Adults with Type 2 Diabetes
Authors: Leite Silmara A O , Bastos Murilo , Silva Michael P , Lavalle Ana C R , Bertogy Maria C V , Kuklik Suelen V , Umpierrez Guillermo 
Published: September 2023

Abstract

Background
The relationship of sarcopenia with relevant features of T2DM and its treatment is inconsistent in the literature.
Aims
To evaluate the prevalence of sarcopenia in insulin treated elderly patients with T2DM.
Methods
A cross-sectional data from a prospective cohort study with T2DM patients aged ≥ 65 y/o on insulin treatment with or without OAD; BMI ≥ 18.5 and ≤ 35 kg/m2; HbA1c ≥ 7.0% and ≤ 9.0%. Exclusion criteria are patients treated with GLP1 agonists; eGFR < 30 (CKD EPI); Hb < 11g / dL; ALT > 3x ULN; glucocorticoid use in the previous 3 months; treatment of current neoplasia; and T1DM. 462 medical records from the database of a public hospital and a private diabetes clinic were selected by medical students who called to invite patients to participate in the study. The European Working Group on Sarcopenia in Older People algorithm was used to evaluate sarcopenia’s presence. This applies to the SARC-F Questionnaire and assessments of muscle strength, skeletal muscle mass, and physical performance.
Results
We evaluated 140 patients aged 71.8 ± 5.4 y/o, 54.3% women and T2DM median duration of 20 years (min 1; max 47); HbA1c = 8.4 ± 1,4%, 87,1% of patients had macrovascular complications history; 42,4% cardiovascular disease; 26.6% retinopathy; 56,4% neuropathy and 92,1% nephropathy. 15,7% had SARC-F score ≥ 4 indicating a high risk of sarcopenia. However, the clinical tests confirmed sarcopenia in 1,4% of the participants.
Conclusions
The prevalence of sarcopenia in this group of elderly people with T2DM on insulin treatment was lower than in the general population.
Sparse Sampling MRI Reconstruction Technique via ANN
Authors: Christilin D M Annie Brighty 
Published: September 2023

Abstract

MRI is a viable tissue of an image. But in slow processing of image acquisition, MRI creates some noisy data. Compressed Sensing is a join mechanism of compression and sensing. So Compressed Sensing method is guiding to decrease the pattern recognition and suppress the some artifacts in MRI. However, MRI has some sparsity image which is obtained by the curvelet transformation and the reconstructed the noise data. But the issue of curvelet transformation is that it could not manipulate the sparse image. So the Patch Based Directional Curvelet Transformation (PBDCT) recovered the problem of that transformation in this research. But sparse sampling is built a hardware which is very difficult. Hence the proposed sparse sampling process is utilized for Artificial Neural Network (ANN) Experimentally, this proposed method is compared with SIDCT and PBDCT based on Signal-to-Noise Ratio (SNR) and Relative L2 Norm Error (RLNE)
A Golden-Free Unsupervised ML-Assisted Security Approach for Detection of IC Hardware Trojans
Authors: Ghimire Ashutosh , Alkurdi Mohammed , Amsaad Fathi , Rehman Md Tauhidur 
Published: September 2023

Abstract
Hardware Trojans are deliberate malicious hardware modifications inserted in semiconductor Integrated circuits (ICs) for the purpose of stealing or leaking sensitive information, as well as disrupting critical systems upon activation, underscoring the importance of robust detection mechanisms. Emerging hardware security research highlight the criticality of employing AI for effective detection within the semiconductor IC supply chain. The efficient detection of these malicious Trojan circuits is of utmost significance, as it holds paramount importance in cultivating trust within the semiconductor IC supply chain. However, prevailing detection methodologies, predominantly reliant on side-channel analysis, often necessitate the utilization of golden chips for validation. This paper heralds a new era in Hardware Trojan detection, harnessing the prowess of unsupervised machine learning in conjunction with side-channel analysis to eliminate the need for golden data. Through FPGA-based experimentation involving Trojans of varying dimensions, the efficacy of this innovative approach was evaluated. Employing unsupervised clustering, the methodology effectively uncovered anomalies. The application of unsupervised learning techniques not only showcased a superior false positive rate but also demonstrated a comparable accuracy level when compared to supervised counterparts such as the K-Nearest Neighbors (KNN) classifier, Support Vector Machine (SVM), and Gaussian classifier—methods reliant on the availability of golden data for training. Notably, the proposed model exhibited an impressive accuracy rate of 93%, particularly excelling in pinpointing diminutive Trojans triggered by concise events, surpassing the capabilities of preceding techniques. In conclusion, this research advances a groundbreaking paradigm in hardware Trojan detection, accentuating its potential in bolstering the integrity of semiconductor IC supply chains.
Assessment of orofacial muscle strength, masticatory and swallowing function in children indicated for orthodontic treatment.
Authors: Aldausari Rayed , Kumar Abhishek , Suzuki Ayumi , Pegelow Marie , Grigoriadis Anastasios 
Published: September 2023

Abstract
Objectives
To evaluate orofacial muscle strength, masticatory and swallowing function in children indicated for orthodontic treatment.
Materials and Method
Sixty-two volunteers were equally divided into an experimental group (mean age:14.9 ± 2.8, 15 girls) and a control group (15.2 ± 2.3, 15 girls) based on their orthodontic treatment needs. The orofacial muscle strength was measured by recording the maximum voluntary bite force (MVBF), tongue and cheek pressure. Additionally, the participants also performed a food comminution and mixing ability tests to measure their masticatory performance. Swallowing function was assessed with a standardized Test of Masticating and Swallowing Solids (TOMASS).
Results
The results showed significant differences in the MVBF (P = 0.009) but no differences in tongue pressure (P = 0.208) and cheek pressure (P = 0.925) between the groups. The results also showed no significant differences in food comminution test and mixing ability test between the two groups (P = 0.553, P = 0.269, respectively). The results of the TOMASS test showed significant differences in the number of bites to eat the cracker (P = 0.003) but no significant differences in number of chewing cycles (P = 0.855), number of swallows (P = 0.149) or duration to eat the cracker (P = 0.275).
Conclusions
Patients indicated for orthodontic treatments show poor orofacial muscle strength in terms of lower MVBF with the age and sex matched controls. However, the patient group does not show any signs of impaired masticatory or swallowing function.
Clinical relevance:
A comprehensive assessment of oral functions in children can enhance clinicians' evaluation of orthodontic treatment needs. MVBF could be a simple and useful tool to evaluate the orthodontic treatment needs.
GroupMO: A Memory-augmented Meta-optimized Model for Group Recommendation
Authors: Yang Wen , Hong Jiawei , Zhao Jing , Fang Junhua , Qu Jianfeng , Chao Pingfu , Zhang Ruoqian 
Published: September 2023

Abstract
Group recommendation aims to suggest desired items for a group of users. Existing methods can achieve inspiring results in predicting the group preferences in data-rich groups. However, they could be ineffective in supporting cold-start groups due to their sparsity interactions, which prevents the model from understanding their intent. Although cold-start groups can be alleviated by meta-learning, we cannot apply it by using the same initialization for all groups due to their varying preferences. To tackle this problem, this paper proposes a memory-augmented meta-optimized model for group recommendation, namely GroupMO. Specifically, we adopt a clustering method to assemble the groups with similar profiles into the same cluster and design a representative group profile memory to guide the preliminary initialization of group embedding network for each group by utilizing those clusters. Besides, we also design a group shared preference memory to guide the prediction network initialization at a more refined granularity level for different groups, so that the shared knowledge can be better transferred to groups with similar preferences. Moreover, we incorporate those two memories to optimize the meta-learning process. Finally, extensive experiments on two real-world datasets demonstrate the superiority of our model.
The adaptive community-response (ACR) method for collecting misinformation on social media
Authors: Kauk Julian , Kreysa Helene , Scherag André , Schweinberger Stefan R 
Published: September 2023

Abstract
Social media can be a major accelerator of the spread of misinformation, thereby potentially compromising both individual well-being and social cohesion. Despite significant recent advances, the study of online misinformation is a relatively young field facing several (methodological) challenges. In this regard, the detection of online misinformation has proven difficult, as online large-scale data streams require (semi-)automated, highly specific and therefore sophisticated methods to separate posts containing misinformation from irrelevant posts. In the present paper, we introduce the adaptive community-response (ACR) method, an unsupervised technique for the large-scale collection of misinformation on Twitter (now known as 'X'). The ACR method is based on previous findings showing that Twitter users occasionally reply to misinformation with fact-checking by referring to specific fact-checking sites (crowdsourced fact-checking). In a first step, we captured such misinforming but fact-checked tweets. These tweets were used in a second step to extract specific linguistic features (keywords), enabling us to collect also those misinforming tweets that were not fact-checked at all as a third step. We initially present a mathematical framework of our method, followed by an explicat algorithmic implementation. We then evaluate ACR on the basis of a comprehensive dataset consisting of > 25 million tweets, belonging to > 300 misinforming stories. Our evaluation shows that ACR is a valid and useful tool for large-scale collection of misinformation online: Text similarity measures clearly indicate correspondence between claims of false stories and collected tweets. Taken together, ACR's efficacy is based upon three pillars: (i) the adoption of prior, pioneering research in the field, (ii) a well-formalized mathematical framework and (iii) a robust empirical proof. This triad leads us to the conclusion that ACR has the potential to make a valuable contribution to further resolve methodological challenges of the field.
An Expert System for Clinical Risk Assessment of Polycystic Ovary Syndrome under Uncertainty
Authors: Karim Rezaul , Khaliluzzaman Md. , Mahmud Tanjim , chy Deepak Kumar 
Published: September 2023

Abstract
This paper describes a prototype clinical expert system for risk stratification of patients with polycystic ovary syndrome (PCOS). Polycystic ovary syndrome (PCOS) is the most common hormonal disorder among women of reproductive age. It is a heterogeneous disorder of uncertain cause. Since the symptoms of PCOS are seemingly unrelated to one another the condition is often overlooked and undiagnosed. The determination of accurate degree or intensity of PCOS signs is difficult for the physician. Hence, the accuracy of the diagnostic process is difficult to achieve. The signs and symptoms of PCOS are usually expressed in qualitative and quantitative ways. Since the qualitative factors cannot measure in a quantitative way, various types of uncertainties may occur, such as incompleteness, vagueness and imprecision. For that, it is necessary to address the issue of uncertainty by using appropriate methodology. However, no existing system is able to address this issue of uncertainty. Therefore, this paper demonstrates the application of a novel method, named belief rule-based inference methodology-RIMER; this prototype can deal with uncertainties in both clinical domain knowledge and clinical data. This paper reports the development of a Belief Rule Based Expert System (BRBES) using RIMER approach, which is capable of detecting the PCOS by taking account of signs and symptoms.
A Workflow to Systematically Design Uncertainty-Aware Visual Analytics Applications
Authors: Maack Robin G. C. , Raith Felix , Perez Juan , Scheuermann Gerik , Gillmann Christina 
Published: September 2023

Abstract
Visual Analytics (VA) is a paradigm for insight generation by using visual analysis techniques and automated reasoning by transforming data into hypotheses and visualization to extract new insights, feeding them back into the data. This enhances the data until the desired insight is found. Many applications use this principle to provide meaningful mechanisms to assist decision-makers in achieving their goals. This process can be affected by a variety of uncertainties that can interfere with the user decision-making process. Unfortunately, there is no methodical description and handling tool to systematically include uncertainty in VA. We provide a unified workflow to transform the classic VA cycle into an uncertainty-aware Visual Analytics (UAVA) cycle consisting of five steps. Three real-world applications represent examples of the implementation of the UAVA cycle and the described workflow to prove its usability.
WSPÓŁCZESNE WYZWANIA EDUKACYJNE W KONTEKŚCIE KRYZYSU EKOLOGICZNO-KLIMATYCZNEGO. EDUKACJA KLIMATYCZNA W POLSCE „W TOKU”
Authors: Gola Beata 
Published: September 2023

Jednym z najpilniejszych wyzwań edukacyjnych w kontekście kryzysu klimatyczno-ekologicznego jest edukacja na rzecz klimatu. Obecnie łączy się ona z edukacją do zrównoważonego rozwoju, edukacją globalną i edukacją konsumencką. Zmiany klimatu przyczyniają się do nierówności i pogłębiania niesprawiedliwości społecznej. Stąd konieczność jednoczesnego przeciwdziałania utracie bioróżnorodności i kryzysowi klimatycznemu oraz ich skutkom społecznym. Pedagogika otwierając się na aktualne, globalne problemy może kształtować filozofię wychowania i kształcenia, wpływać na politykę edukacyjną, programy szkolne etc. Humanistyka ekologiczna, także za sprawą pedagogiki, może tworzyć perspektywę zmiany współczesnych paradygmatów na takie, w których w większym stopniu dostrzeżona zostanie nieinstrumentalna wartość istot pozaludzkich i potrzeba integralnej troski o całą biosferę. W artykule przedstawione zostaną rekomendacje Okrągłego Stołu w zakresie edukacji klimatycznej w Polsce.
PARENT-CHILD RELATIONSHIPS IN THE CONTEXT OF EARLY READING INITIATIONS
Authors: Kuracki Kamil , Dłużniewska Agnieszka 
Published: September 2023

W artykule podjęto problematykę dotyczącą znaczenia relacji rodzic-dziecko dla zaangażowania rodziców w podejmowanie wspólnych inicjacji czytelniczych z dziećmi. Badania ilościowe przeprowadzone w grupie rodziców dzieci ze specjalnymi potrzebami rozwojowymi (N=198) oraz bez specjalnych potrzeb rozwojowych (N=194) pozwoliły na ustalenie związków pomiędzy deklarowanym przez obie badane grupy rodziców zaangażowaniem w podejmowanie wczesnych inicjacji czytelniczych a przejawianymi przez nich zachowaniami wspierającymi lub przymusowymi, samooceną własnych zachowań w kontakcie z dzieckiem oraz oceną zachowań dziecka, a także na rozpoznanie predyktorów zaangażowania rodziców dzieci ze specjalnymi potrzebami rozwojowymi i bez specjalnych potrzeb rozwojowych w podejmowanie wspólnych inicjacji czytelniczych z dziećmi. Wyniki badań wskazują m.in., że głównym predyktorem zaangażowania rodziców w podejmowanie wspólnych inicjacji czytelniczych w obu badanych grupach są działania wspierające/zaangażowane. Dodatkowo w grupie rodziców ze specjalnymi potrzebami rozwojowymi wskazano na mediacyjną rolę dokonywanej przez rodziców dzieci ze specjalnymi potrzebami rozwojowymi oceny zachowań dziecka w relacji między ujawnianymi przez nich zachowaniami wspierającymi/zaangażowanymi a zaangażowaniem w podejmowanie wczesnych inicjacji czytelniczych z dziećmi.
Astragaloside IV Regulates Insulin Resistance and Inflammatory Response
of Adipocytes via Modulating MIR-21/PTEN/PI3K/AKT Signaling
Authors: Guo Xuxi , Yin Taoqing , Chen Dongni , Xu Shuai , Ye Renqun , Zhang Yue 
Published: September 2023

Background:
The progression of Type 2 Diabetes Mellitus (T2DM) can lead to various complications. Compounds derived from natural products have been found to be effective in com-batting T2DM. This study aimed to investigate the effects of Astragaloside IV (AS-IV) on insulin resistance and the inflammatory response of adipocytes. The study also aimed to determine the downstream signaling pathways involved.

Materials and Methods:
The glucose consumption of adipocytes was assessed using a glucose assay kit. qRT-PCR, Western blot, and ELISA assays were used to measure mRNA and protein levels. The interaction between miR-21 and PTEN was assessed using a Dual-luciferase reporter assay.

Results:
The results showed that AS-IV increased glucose consumption and the expression of GLUT-4 in adipocytes with insulin resistance in a concentration-dependent manner. However, AS-IV decreased the protein levels of TNF-α and IL-6 in these cells. Additionally, AS-IV up-regulated miR-21 expression in adipocytes with insulin resistance in a concentration-dependent manner. Fur-thermore, miR-21 overexpression increased glucose consumption and GLUT-4 expression but de-creased TNF-α and IL-6 protein levels in adipocytes. Conversely, miR-21 inhibition attenuated the AS-IV-induced increase in glucose consumption and GLUT-4 expression and the decrease in TNF-α and IL-6 protein levels in adipocytes. MiR-21 also inversely regulated PTEN in adipocytes, and PTEN overexpression had effects similar to miR-21 inhibition in AS-IV-treated adipocytes. Fi-nally, AS-IV up-regulated p-PI3K and p-AKT protein expression in adipocytes, which was atten-uated by miR-21 inhibition.

Conclusion:
The study concluded that AS-IV attenuated insulin resistance and the inflammatory response in adipocytes. The mechanistic studies indicated that AS-IV modulated the miR-21/PTEN/PI3K/AKT signaling in adipocytes to exert these effects.