Miracle-dz/UniFAR-FTUs huggingface dataset:
Analisis Pengendalian Kualitas Dengan Metode Seven Tools Dan Kaizen Dalam Upaya Mengurangi Tingkat Kecacatan Produk

Pabrik Roti Bakar Azhari merupakan UMKM yang berdomisili di Rejowinangun, kotagede, Kota Yogyakarta. Dalam proses produksi roti tidak dapat dipungkiri akan terjadi kecacatan produk. Dalam 1 bulan, pabrik ini mampu memproduksi sebanyak 15330 roti dan dalam produksi tersebut terdapat 356 pcs roti yang cacat. Cacat tersebut diantaranya adalah roti gosong, roti tidak mengembang sempurna dan pori pori roti besar. Tujuan dari penelitian ini adalah untuk mengetahui usulan perbaikan dengan metode seven tools dan kaizen. Teknik pengumpulan data yang digunakan yaitu data primer dan data sekunder. Hasil dari penelitian ini adalah Pabrik Roti Bakar Azhari menghasilkan roti gosong sebanyak 79 pcs dengan presentase cacat sebesar (22.19%), roti kurang mengembang sebanyak 204 pcs dengan presentase cacat (57.30%), dan pori pori roti besar sebanyak 73 pcs dengan presentase cacat (20.51%). Berdasarkan hasil analisis dapat dijadikan usulan perbaikan untuk mengurangi kecacatan produk dengan pembuatan SOP dan perubahan tata letak layout pabrik.
Scratching a soft layer above a hard substrate

ABSTRACT Soft layers may develop on a harder substrate during tribological processes. We perform molecular dynamics simulations of a model system, in which a hard substrate covered by a 4-nm thick soft layer is indented and scratched with a spherical tip along the surface. When scratching at a depth of only d = 2 nm – i.e. fully in the soft layer – the friction coefficient μ is the same as in a homogeneous (purely soft or hard) material; this is expected since in the ploughing regime, the friction coefficient of a sphere depends only on the indentation depth but not on the material. When scratching at d = 4 nm – i.e. at the interface between soft and hard material – μ of the bilayer material is strongly reduced compared to both the soft and the hard material. This reduction is caused by the fact that the scratching force is similar to that in a purely soft material, while the normal force is increased towards its value in the hard material. This effect also persists when scratching at d = 6 nm.
Food sufficiency, an approach rooted in the ethics of Epicurus: Analysis framework and research agenda

Against the backdrop of an ecological crisis, we must transform our consumption patterns to ensure long-term sustainability. By reducing the negative impact of our food on health and the social and biospheric environment, food sufficiency is one way to achieve this transformation. However, this raises a major question about the compatibility of food sufficiency with pleasure – that is, one traditional pillar of ‘eating well’. At the crossroads of philosophy and marketing, this theoretical research draws on Epicurus’s ethics to address this issue. It highlights the importance of Epicurean consumer value as a fundamental element of both individual and collective ‘eating well’. In addition, it proposes an analysis framework that shows how an approach to food sufficiency that prioritises the satisfaction of essential needs can provide access to this value. Finally, the article proposes a detailed research agenda that outlines research avenues and managerial implications.
A Monocular SLAM System Based on ResNet Depth Estimation

Currently, monocular simultaneous location and mapping (SLAM) systems cannot extract depth information from monocular cameras directly and require initialization to solve the problem of scale uncertainty. It is extremely difficult to reconstruct maps using such systems, and it is difficult to cope with scenarios that require navigation and obstacle avoidance. In order to solve the above problems, in this article, a simple monocular depth estimation network framework is proposed. Transfer learning from a pre-trained ResNet is utilized for the encoding part of the framework and a convolutional neural network (CNN) is used for the decoding part. Only a few training parameters and iterations are required to obtain fairly accurate depth information. At the same time, a similarity-based filter is used to denoise the surfels and improve the red green blue-depth (RGB-D) SLAM system, which not only reduces the impact of the depth estimation error on the surfels but also ensures the quality of the dense mapping. From the results of comparative experiments, it can be seen that the proposed monocular depth estimation network framework is better than current popular methods, and the associated SLAM system can achieve pose estimation and dense mapping tasks. As a monocular camera-based SLAM system, the proposed method is a promising and practical approach.
Study for Image Fusion Based on Wavelet Transform

An algorithm of image fusion based on wavelet transform is proposed. Firstly, the obtained multi-source images which are registered are decomposed into several coefficients of low frequency and high frequency by using wavelet transform. Secondly, the wavelet coefficients of multi-source images are fused by different fusion rules based on regional features. Finally, the fusion image is obtained by inverse wavelet transform. Lots of experiments and comparisons with other fusion methods show that the effectiveness and superiority of image fusion method based on wavelet transform.
Evaluation of online video content related to reverse shoulder arthroplasty: a YouTube-based study

Background Reverse shoulder arthroplasty (RSA) has evolved continuously over recent years, with expanded indications and better outcomes. YouTube is one of the most popular sources for health-related information available to patients. Evaluating the quality of YouTube videos concerning RSA is important to ensure proper patient education. Methods YouTube was queried for the term “reverse shoulder replacement. ” The first 50 videos were evaluated using three different scores: Journal of the American Medical Association (JAMA) benchmark criteria, the global quality score (GQS), and the reverse shoulder arthroplasty-specific score (RSAS). Multivariate linear regression analyses were conducted to determine the presence of a relationship between video characteristics and quality scores. Results The average number of views was 64,645.78±264,160.9 per video, and the average number of likes was 414 per video. Mean JAMA, GQS, and RSAS scores were 2.32±0.64, 2.31±0.82, and 5.53±2.43, respectively. Academic centers uploaded the highest number of videos, and surgical techniques/approach videos was the most common video content. Videos with lecture content predicted higher JAMA scores whereas videos uploaded by industry predicted lower RSAS scores. Conclusions Despite its massive popularity, YouTube videos provide a low quality of information on RSA. Introducing a new editorial review process or developing a new platform for patients’ medical education may be necessary. Level of evidence Not applicable.
Navigating Cisgenderism: The Experiences of Three Gender-Expansive Music Educators

With the intent of improving music teacher education for people of trans and/or gender-expansive (TGX) experience, the purpose of this study is to convey the voices and experiences of three TGX music educators. These data are drawn from four semi-structured interviews with three participants totaling 268 min. Utilizing transgender theory and cisgenderism as theoretical frameworks, four major categories arose during data analysis: (a) modes of disclosure, (b) building safe space, (c) negative experiences, and (d) policy. While these three teachers found support at school, they also faced difficulties and policies that affected their careers and decisions about disclosure of their gender identity. For example, all three participants expressed concerns about parent backlash. Drawing upon the participants’ stories, I explore how music teacher educators can better support TGX students navigate cisgenderism. In addition, music teacher educators can gain perspective on how policy decisions can influence the careers of TGX music educators.
PATTERN – Pathfinding Algorithms To Tackle Effective Route Navigation

Food and parcel delivery routing is a major problem area due to its dynamism and complexity, exacerbated in recent years by growth in demand. The problem was modelled as a variation of the OP, a classical combinatorial optimisation problem, specifically the OTOP, involving a team of vehicles where each vehicle has a time budget to serve locations. A hybridisation of the metaheuristics Simulated Annealing and Iterated Local Search (SAILS) was constructed, able to escape local optima by sometimes accepting worse solutions. A website was also created to showcase the algorithm and computational tests were conducted on instances with varying parameters to simulate the large breadth of real-world scenarios. SAILS had higher profit than ILS and the initial solution and was able to acquire 58.8% of the profit increase over 20 minutes of runtime within 5 seconds, showing efficiency. However, the low improvement of SAILS over ILS shows SAILS has much room for improvement. Possible future work includes creating a more representative model with fewer assumptions and improving the algorithm through methods like reheating, genetic algorithms, and more precise parameter tuning. In short, a SAILS pathfinding algorithm was constructed to effectively and efficiently tackle delivery routing.
Assessment of Aptamer as a Potential Drug Targeted Delivery for Retinal Angiogenesis Inhibition

AT11-L0 is an aptamer derivative of AS1411 composed of G-rich sequences that can adopt a G-quadruplex (G4) structure and target nucleolin (NCL), a protein that acts as a co-receptor for several growth factors. Hence, this study aimed to characterize the AT11-L0 G4 structure and its interaction with several ligands for NCL targeting and to evaluate their capacity to inhibit angiogenesis using an in vitro model. The AT11-L0 aptamer was then used to functionalize drug-associated liposomes to increase the bioavailability of the aptamer-based drug in the formulation. Biophysical studies, such as nuclear magnetic resonance, circular dichroism, and fluorescence titrations, were performed to characterize the liposomes functionalized with the AT11-L0 aptamer. Finally, these liposome formulations with the encapsulated drugs were tested on the human umbilical vein endothelial cell (HUVEC) model to assess their antiangiogenic capacity. The results showed that the AT11-L0 aptamer–ligand complexes are highly stable, presenting melting temperatures from 45 °C to 60 °C, allowing for efficient targeting of NCL with a KD in the order of nM. The aptamer-functionalized liposomes loaded with ligands C8 and dexamethasone did not show cytotoxic effects in HUVEC cells compared with the free ligands and AT11-L0, as assessed by cell viability assays. AT11-L0 aptamer-functionalized liposomes encapsulating C8 and dexamethasone did not present a significant reduction in the angiogenic process when compared with the free ligands. In addition, AT11-L0 did not show anti-angiogenic effects at the concentrations tested. However, C8 shows potential as an angiogenesis inhibitor, which should be further developed and optimized in future experiments.
An Internet of Things based approach for Smart Home Management

The advent of the Internet of Things (IoT) paradigm has led to the construction of technological environments based on device communication. In this scenario, solutions have been developed for the intelligent management of various services, such as those related to Smart Cities. In such a scenario, widespread use is that of Smart Homes, environments that can provide management help and intelligent and tailored services to users. This paper aims to present an Internet of Things-based approach to Smart Home management. The proposed approach, which leverages graph approaches, enables the extraction and processing of contextual data, collected from sensors, and probabilistic approaches able to provide valuable information and autonomous actions. The system training phase is performed using graph approaches, which could represent an increase in Context and Situation Awareness. In the experimental phase, a prototype is used to test the proposed method’s energysaving and ventilation management capabilities, which shows encouraging findings.
Checking Default Correlation and Score Correlation in a Breakpoint Model for Rating Classification

In credit risk, debtors with different creditworthiness are divided into rating classes. One problem is to define the borders of the rating classes. A natural way to estimate these breakpoints from default observations comes out of the field of change point analysis. In order to account for dependency between the debtors, the literature proposes a combination of a breakpoint model with a one-factor model. One finds strongly consistent estimators for the threshold of the rating classes and the corresponding default probabilities, also called risk levels. But an investigation of the inherent model properties is as yet missing. For this reason we derive the default correlation and study its relationship to the model parameters, i.e., the breakpoint, the risk levels, and a new correlation term, named score correlation, appearing in a simulation study. Eventually, we check the magnitude of the score correlation used in the simulation study.
Multilevel Feature Aggregated Network with Instance Contrastive Learning Constraint for Building Extraction

Building footprint extraction from remotely sensed imagery is a critical task in the field of illegal building discovery, urban dynamic monitoring, and disaster emergency response. Recent research has made significant progress in this area by utilizing deep learning techniques. However, it remains difficult to efficiently balance the spatial detail and rich semantic features. In particular, the extracted building edge is often inaccurate, especially in areas where the buildings are densely distributed, and the boundary of adjacent building instances is difficult to distinguish accurately. Additionally, identifying buildings with varying scales remains a challenging problem. To address the above problems, we designed a novel framework that aggregated multilevel contextual information extracted from multiple encoders. Furthermore, we introduced an instance constraint into contrastive learning to enhance the robustness of the feature representation. Experimental results demonstrated that our proposed method achieved 91.07% and 74.58% on the intersection over union metric on the WHU and Massachusetts datasets, respectively, outperforming the most recent related methods. Notably, our method significantly improved the accuracy of building boundaries, especially at the building instance level, and the integrity of multi-scale buildings.
The Number of Solutions of Congruences in Incomplete Residue Systems

Let denote the set of points x = (x 1, . . . , xn ) with integral co-ordinates in Euclidean n-space. For any fixed integer m ≥ 2, let C = C(m) be the set of such points in the cube 0 ≤ xi < m (i = 1, 2, . . . , n) and let be any subset of C. Suppose that f(x) is any single-valued, integral-valued function, defined for all x ∊ . We consider solutions x ∊ of the congruence
A Bayesian Multivariate Gametic Model in a Reciprocal Cross with Genomic Information: An Example with Two Iberian Varieties

Simple Summary INGA FOOD, S.A. initiated a crossbreeding program involving two Iberian pig varieties: Retinto and Entrepelado. The primary objective of this program is to produce an F1 hybrid sow that exhibits enhanced reproductive performance. In a previous investigation, variations in the reproductive performance of sows, specifically litter size, were observed among the reciprocal crosses. These variations indicate the presence of genomic imprinting effects. To assess the influence of genetic origin, we developed a multivariate gametic model to estimate the gametic correlations between paternal and maternal effects. Gametic correlations lower than one could potentially explain the performance differences observed across the reciprocal crosses. Despite having limited data, the study’s findings suggest that the gametic correlation estimate between paternal and maternal effects on litter size is lower in the Entrepelado population compared to the Retinto population. Abstract INGA FOOD, S.A. initiated a crossbreeding program between two Iberian pig varieties, Retinto (R) and Entrepelado (E), with the goal of producing a hybrid sow (F1). Several studies have been conducted to evaluate its productive performance, and these studies have revealed differences in litter size between the two reciprocal crosses, suggesting the presence of genomic imprinting effects. To further investigate these effects, this study introduces a multivariate gametic model designed to estimate gametic correlations between paternal and maternal effects originating from both genetic backgrounds involved in the reciprocal crosses. The dataset consisted of 1258 records (the total number born—TNB and the number born alive—NBA) from 203 crossbred dams for the Entrepelado (sire) × Retinto (dam) cross and 700 records from 125 crossbred dams for the Retinto (sire) × Entrepelado (dam) cross. All animals were genotyped using the GeneSeek® GPP Porcine 70 K HDchip (Illumina Inc., San Diego, CA, USA). The results indicated that the posterior distribution of the gametic correlation between paternal and maternal effects was distinctly different between the two populations. Specifically, in the Retinto population, the gametic correlation showed a positive skew with posterior probabilities of 0.78 for the TNB and 0.80 for the NBA. On the other hand, the Entrepelado population showed a posterior probability of a positive gametic correlation between paternal and maternal effects of approximately 0.50. The differences in the shape of the posterior distribution of the gametic correlations between paternal and maternal effects observed in the two varieties may account for the distinct performance outcomes observed in the reciprocal crosses.
High-flux monochromatic ion and electron beams based on laser-cooled atoms

L. Kime,1,2 A. Fioretti,1,4,5 Y. Bruneau,1 N. Porfido,4 F. Fuso,4 M. Viteau,2 G. Khalili,1 N. Šantić,1 A. Gloter,3 B. Rasser,2 P. Sudraud,2 P. Pillet,1 and D. Comparat1 1Laboratoire Aimé Cotton, CNRS, Université Paris-Sud, ENS Cachan, Bât. 505, 91405 Orsay, France 2Orsay Physics, 95 Avenue des Monts Auréliens, ZA Saint-Charles, 13710 Fuveau, France 3Laboratoire de Physique des Solides, UMR 8502, Université Paris-Sud, Bât. 510, 91405 Orsay, France 4Dipartimento di Fisica, Universitá di Pisa and CNISM, Largo Pontecorvo 3, 56127 Pisa, Italy 5Istituto Nazionale di Ottica, INO-CNR, U.O. S. Pisa “Adriano Gozzini,” via Moruzzi 1, 56124 Pisa, Italy (Received 1 November 2012; revised manuscript received 25 August 2013; published 30 September 2013)
Device to Device based Delay Tolerant Networks with Group Priority for Disaster
 Information Systems

The East Japan Great Earthquake in 2011 brought various damages such as the delay of rescue,the heavy traffic jam, and the shortage of rations because of the heavy damages of the informationnetworks. Therefore, this paper proposed the D2D (Device-to-Device) based DTN (Delay TolerantNetworks) for Disaster Information Systems. The methods consist of the D2D wireless connectioncontrols with the group priority that is based on the historical locational data and the Data Triagemethod that is the data priority functions based on the user policy when the device transmits the data.Then, the results are discussed by the experimental data using the prototype system, and also thefuture works for the usages of the vehicle to vehicle communication are discussed.
Ion correlation and negative lithium transference in polyelectrolyte solutions

Polyelectrolyte solutions (PESs) recently have been proposed as high conductivity, high lithium transference number (t+) electrolytes where the majority of the ionic current is carried by the electrochemically active Li-ion. While PESs are intuitively appealing because anchoring the anion to a polymer backbone selectively slows down anionic motion and therefore increases t+, increasing the anion charge will act as a competing effect, decreasing t+. In this work we directly measure ion mobilities in a model non-aqueous polyelectrolyte solution using electrophoretic Nuclear Magnetic Resonance Spectroscopy (eNMR) to probe these competing effects. While previous studies that rely on ideal assumptions predict that PESs will have higher t+ than monomeric solutions, we demonstrate that below the entanglement limit, both conductivity and t+ decrease with increasing degree of polymerization. For polyanions of 10 or more repeat units, at 0.5 m Li+ we directly observe Li+ move in the “wrong direction” in an electric field, evidence of a negative transference number due to correlated motion through ion clustering. This is the first experimental observation of negative transference in a non-aqueous polyelectrolyte solution. We also demonstrate that t+ increases with increasing Li+ concentration. Using Onsager transport coefficients calculated from experimental data, and insights from previously published molecular dynamics studies we demonstrate that despite selectively slowing anion motion using polyanions, distinct anion–anion correlation through the polymer backbone and cation–anion correlation through ion aggregates reduce the t+ in non-entangled PESs. This leads us to conclude that short-chained polyelectrolyte solutions are not viable high transference number electrolytes. These results emphasize the importance of understanding the effects of ion-correlations when designing new concentrated electrolytes for improved battery performance.
A model for k-out-of-m load-sharing systems

ABSTRACT In a load-sharing system, the failure of a component affects the residual lifetime of the surviving components. We propose a model for the load-sharing phenomenon in k-out-of-m systems. The model is based on exponentiated conditional distributions of the order statistics formed by the failure times of the components. For an illustration, we consider two component parallel systems with the initial lifetimes of the components having Weibull and linear failure rate distributions. We analyze one data set to show that the proposed model may be a better fit than the model based on sequential order statistics.
Effects of Microwave Pasteurization on the Quality and Shelf-Life of Low-Sodium and Intermediate-Moisture Pacific Saury (Cololabis saira)

The objective of this study was to investigate the effects of microwave pasteurization on the quality and shelf-life of low-sodium and intermediate-moisture Pacific saury. Microwave pasteurization was used to process low-sodium (1.07% ± 0.06%) and intermediate-moisture saury (moisture content 30% ± 2%, water activity 0.810 ± 0.010) to produce high-quality ready-to-eat food stored at room temperature. Retort pasteurization with the same thermal processing level of F90 = 10 min was used for comparison. Results showed that microwave pasteurization had significantly (p < 0.001) shorter processing times (9.23 ± 0.19 min) compared with traditional retort pasteurization (17.43 ± 0.32 min). The cook value (C) and thiobarbituric acid (TBARS) content of microwave-pasteurized saury were significantly lower than that of retort-pasteurized saury (p < 0.05). With more microbial inactivation, microwave pasteurization brought better overall texture than retort processing. After 7 days of storage at 37 °C, the total plate count (TPC) and TBARS of microwave pasteurized saury still met the edible standard, while the TPC of retort pasteurized saury no longer did. These results showed that the combined processing of microwave pasteurization and mild drying (Aw < 0.85) could produce high-quality ready-to-eat saury products. These results indicate a new methodology for producing high-quality products stored at room temperature.