Miracle-dz/UniFAR-FTUs huggingface dataset:
Earthquakes as a potential contributing factor to climate change at multi-decadal scale

Climate changes at the multi-decadal scale are often associated with multi-decadal phase shifts of the dominant sea surface temperature (SST) pattern, such as the Pacific Decadal Oscillation (PDO). The PDO may be associated with the North Pacific branch of the Thermohaline Circulation (THC). Great earthquakes (M >8), particularly along the route of the THC, might modulate the vertical mixing and bring deep, cold water to surface, contributing to multi-decadal changes in surface currents and the PDO. This may eventually lead to multi-decadal climate changes. We tested this hypothesis for the Pacific Ocean where great earthquakes have been frequently recorded. We found associations between the PDO and recurrent earthquakes along the route of the deep currents of the THC in the modern period since 1900, and relationships between hydroclimate change in Monsoonal Asia and historical earthquakes since 1300. However, it should be noted that this hypothesis is very preliminary and has many gaps that needs further evidences from more observational records and modeling studies.
Exponential spatial correlation with large‐scale fading variations in massive MIMO channel estimation

To provide the vast exploitation of the large number of antennas on massive multiple‐input–multiple‐output (M‐MIMO), it is crucial to know as accurately as possible the channel state information in the base station. This knowledge is canonically acquired through channel estimation procedures conducted after a pilot signaling phase, which adopts the widely accepted time‐division duplex scheme. However, the quality of channel estimation is very impacted either by pilot contamination or by spatial correlation of the channels. There are several models that strive to match the spatial correlation in M‐MIMO channels, the exponential correlation model being one of these. To observe how the channel estimation and pilot contamination are affected by this correlated fading model, this work proposes to investigate an M‐MIMO scenario applying the standard minimum mean square error channel estimation approach over uniform linear arrays and uniform planar arrays (ULAs and UPAs, respectively) of antennas. Moreover, the elements of the array are considered to contribute unequally on the communication, owing to large‐scale fading variations over the array. Thus, it was perceived that the spatially correlated channels generated by this combined model offer a reduction of pilot contamination, consequently the estimation quality is improved. The UPA acquired better results regarding pilot contamination since it has been demonstrated that this type of array generates stronger levels of spatial correlation than the ULA. In contrast to the favorable results in channel estimation, the channel hardening effect was impaired by the spatially correlated channels, where the UPA imposes the worst performance of this effect for the discussed model.
Growth and Development of Black-Boned Chicken Embryonic Stem Cells for Culture Meat using Different Serums as Medium

This research was conducted to investigate the growth performance of black-boned chicken embryonic stem (ES) cells for the future development of cultured meat. Black-boned chicken ES cells were isolated and cultured from fertilized eggs. The treatments applied were: fetal bovine serum (FBS) (T1), commercial chicken serum (SCK) (T2), Pradu Hang Dam chicken serum (PDC) (T3), and black-boned chicken serum (BBC) (T4). Black-boned chicken ES cells were cultured at 37.0 °C in a humidified environment of 5% CO 2 , for 10 days. The growth of black-boned chicken ES cells concentration was measured by the absorbance at 450 nm. A haemocytometer was used to count the number of black-boned chicken ES cells. Comparing the protein content of cultured meat and chicken meat was collected for combustion and proximate analysis. All collected data were analyzed using ANOVA in a completely randomized design. T4 tended to have a higher number and growth rate than the other groups, followed by T3, T2, and T1, respectively. When counted ES cells final, T4 had a significantly higher number and growth rate than the other groups (p<0.001). Comparing the protein content, it was found that cultured meat had significantly more protein than the other groups (p<0.001), and characteristics (alignment and cross-section of muscle fibers) were not different from chicken cells. Finally, the cultivation of black-boned chicken ES cells necessitates the use of a medium containing black-boned chicken serum in the growth and development of black-boned Chicken ES cells for culture meat.
Spencer's Pathology of the Lung

ABSTRACT In the beginning there was Spencer, and since the last edition in 1985 we have seen two editions of Dail and Hammar and two editions of Thurlbeck and Churg. Whereas new editions of some of the larger books are splitting into two volumes, Spencer's Pathology of the Lung has recombined the two volumes of the fourth edition into a single large volume of 1283 pages, which compares in size with its two competitors. Herbert Spencer was the sole author of the last edition, an impossible act to follow, and Dr Hasleton has recruited 32 contributors from six countries for the new edition. The majority are British, and Hasleton himself is an author on 17 of the 36 chapters, the single author on 10 of these.Although Hasleton and the late Professor Spencer started to write the fifth edition together, and it still bears Spencer's name, it must now be regarded
An Efficient Vision Transformer Model for PCB Component Classification

Printed circuit board (PCB) assemblies in everyday electronic devices are mass-produced. As a result of this production volume, a fast way of visual inspection is necessary. An integral part of visual inspection systems is PCB component classification. In this paper, we have explored use of the Vision Transformer (ViT), which is a recent state-of-the-art image classification approach, for PCB component classification. We have employed several ViT models that are available in the literature and also proposed a new compact, efficient, and high performing ViT model, named as ViT-Mini. We have conducted extensive experiments on the FICS-PCB dataset in order to comparatively evaluate the ViT models' performance. The highest achieved accuracy is 99.46% for capacitor and resistor classification and 96.52% for classification of capacitor, resistor, inductor, transistor, diode, and IC. The proposed compact model's performance is comparable with the ones obtained with larger models, which indicates its suitability for real-time applications.
Efficient Hybrid Method of FEA-Based RSM and PSO Algorithm for Multi-Objective Optimization Design for a Compliant Rotary Joint for Upper Limb Assistive Device

This paper proposes an efficient hybrid methodology for multi-objective optimization design of a compliant rotary joint (CRJ). A combination of the Taguchi method (TM), finite element analysis (FEA), the response surface method (RSM), and particle swarm optimization (PSO) algorithm is developed to solving the optimization problem. Firstly, the TM is applied to determine the number of numerical experiments. And then, 3D models of the CRJ is built for FEA simulation, and mathematical models are formed using the RSM. Subsequently, the suitability of the regression equation is assessed. At the same time, the calculation of weight factors is identified based on the series of statistical equations. Based on the well-established equations, a minimum mass and a maximum rotational angle are simultaneously optimized through the PSO algorithm. Analysis of variance is used to analyze the contribution of design variables. The behavior of the proposed method is compared to the adaptive elitist differential evolution and cuckoo search algorithm through the Wilcoxon signed rank test and Friedman test. The results determined the weight factors of the mass and rotational angle are about 0.4983 and 0.5017, respectively. The results found that the optimum the mass and rotational angle are 0.0368 grams and 59.1928 degrees, respectively. It revealed that the maximum stress of 335 MPa can guarantee a long working time. The results showed that the proposed hybrid method outperforms compared to other evolutionary algorithms. The predicted results are close to the validation results. The proposed method is useful for related engineering fields.
MORPHOMETRIC ANALYSIS OF THE SACRAL HIATUS IN INDIANS: ITS CLINICAL IMPORTANCE

Address for Correspondence: Sarika Rachel Tigga, Department of Anatomy, ESIC Medical College and Hospital, NH-3, NIT, Faridabad, Haryana, India. Mobile: 9891466140 E-Mail: sarika.rachel@gmail.com Introduction: Sacral hiatus (SH) is a significant landmark during caudal epidural block (CEB) which is employed for analgesia and anaesthesia during a wide range of clinical conditions. This requires a thorough knowledge of morphometric characteristics of SH and surrounding landmarks, but variability in morphometric dimensions exists among different populations. Aim: The aim of this study was to identify different anatomical landmarks to detect the location of SH and provide a reference database for morphometric dimensions of SH in Indian population. Materials and Methods: The study was done on 108 dry adult human sacra. Linear measurements of the sacra were taken with the help of digital vernier caliper and angular parameters were determined with a goniometer. Results: The most common shape of the sacral hiatus was inverted ’V’ shaped (59.3%) with the level of the apex at S4 in 66.7% and base at S5 in 86.1% cases. Morphometric dimensions of SH were found to be smaller in present study as compared to reports by other researchers. Left crest-apex angle was observed to be significantly greater than the right crest-apex angle. (p 0.001). Conclusion: Multiple bony landmarks and their morphometric dimensions should be considered to locate the SH during CEB. Values for various morphometric parameters of SH are less in Indians in comparison to other populations, which should be contemplated during caudal epidural injections and trans-sacral thecaloscopy.
On the Use of Kinect V2 For the Assessment of Upper Extremity Movements

Upper extremity assessment is an important step in rehabilitation and treatment of upper extremity impairments. Current assessment methods are mostly based on likert type scales. For example, Fugl-Meyer test is one of the common but subjective tests for upper extremity assessment. The aim of this study is to test the reliability of Kinect V2 camera as an assessment tool of upper extremity movements in the FuglMeyer test. Thirty volunteers participated in the study performed ten upper extremity movements in front of a Kinect V2 camera. After data acquisition, collected data is used to calculate the joint angles. Calculated angle values are examined in terms of relative reliability via Intraclass Correlation Coefficient (ICC), and absolute reliability via Standard Error of Measurement (SEM), Minimum Detectable Change (MDC) for both within-day, and between-days measurements. Results indicate that Kinect V2 provides good to excellent ICC values for within-day, and medium to good ICC values for betweendays. In addition, Kinect V2 has higher absolute reliability in within-day measurements than between-days measurements.
Age Bias: A Tremendous Challenge for Algorithms in the Job Candidate Screening Process

As societies grow older, a growing percentage of workers over the traditional retirement age are choosing to remain in the workforce. However, age discrimination against older workers seeking new job opportunities is prevalent. We conducted a study that asked participants to rate resumes of job candidates from various backgrounds for an IT job position. We found age bias, or ageism, in hiring decisions is implicit and more prevalent than other well-reported forms of bias, such as race or gender biases, yet ageism is also far more difficult for job candidate search algorithms to ignore. In this paper, we examine the challenges of age biases in job hiring algorithms and discuss various steps that can be taken to mitigate them.
Question Answering Versus Named Entity Recognition for Extracting Unknown Datasets

Dataset mention extraction is a difficult problem due to the unstructured nature of text, the sparsity of dataset mentions, and the various ways the same dataset can be mentioned. Extracting unknown dataset mentions which are not part of the training data of the model is even harder. We address this challenge in two ways. First, we consider a two-step approach where a binary classifier filters out positive contexts, i.e., detects sentences with a dataset mention. We consider multiple transformer-based models and strong baselines for this task. Subsequently, the dataset is extracted from the positive context. Second, we consider a one-step approach and directly aim to detect and extract a possible dataset mention. For the extraction of datasets, we consider transformer models in named entity recognition (NER) mode. We contrast NER with the transformers’ capabilities for question answering (QA). We use the Coleridge Initiative “Show US the Data” dataset consisting of $14.3k$ scientific papers with about $35k$ mentions of datasets. We found that using transformers in QA mode is a better choice than NER for extracting unknown datasets. The rationale is that detecting new datasets is an out-of-vocabulary task, i.e., the dataset name has not been seen once during training. Comparing the two-step versus the one-step approach, we found contrasting strengths. A two-step dataset extraction using an MLP for filtering and RoBERTa in QA mode extracts more dataset mentions than a one-step system, but at the cost of a lower F1-score of 62.7%. A one-step extraction with DeBERTa in QA achieves the highest F1-score of 92.88% at the cost of missing dataset mentions. We recommend the one-step approach for the case when accuracy is more important, and the two-step approach when there is a postprocessing mechanism for the extracted dataset mentions, e.g., a manual check. The source code is available at https://github.com/yousef-younes/dataset_mention_extraction.
THE APPLICATION OF SIX SIGMA TO IMPROVE THE YIELD OF PLASTIC INJECTION MOLDING

Plastic injection molding has complex process parameters. The Six Sigma improvement method mainly uses quality control and statistical methods to improve product quality, so as to reduce the cost and waste caused by defective products. Taiwan is the world leader for original equipment manufacturing in the laptop industry, and related peripheral accessories are also a major concern of customers. The subject of this study was a professional supplier of laptop batteries. Through the collection of customer complaint data, it was found that battery case deformation was the most important problem for customers. Therefore, in order to remain competitive, the battery case deformation problem needed to be overcome first. Enterprises need to improve their existing processes to reduce the rate of product defects, improve output efficiency and product quality, and reduce production costs, so as to improve their competitiveness in the industry.This study took a Taiwanese company as an example to improve the plastic injection process through the improvement steps of Six Sigma. In this process, two key process factors, namely the injection speed and the cooling time, were identified by analytical tools. After calculating customers’ daily product demand, the most suitable parameters were found using the ‘design of experiments’ method. The results showed that the process capacity and product yield could be significantly improved. The key to the success of this Six Sigma project was the project implementer’s design of the experiment.
AI in Healthcare: Opportunities and Challenges for Personalized Medicine and Disease Diagnosis

Artificial intelligence (AI) has the potential to revolutionize healthcare by enabling personalized medicine and improving disease diagnosis. This research study explores the latest AI algorithms and applications in healthcare, highlighting their ability to provide faster and more accurate predictions, risk stratification, and improved outcomes through augmented intelligence. However, challenges related to data privacy, ethics, and regulation must be addressed. By leveraging the benefits of AI while addressing these challenges, this study presents an innovative perspective on the transformative potential of AI in healthcare.
Sea ice diatoms and ice edge planktonic diatoms at the northern limit of the Weddell Sea pack ice

Drifting brash ice and phytoplankton were collected between Ele­ phant Island and South Orkney Islands during the period from late December 1988 to mid-January 1989. In diatom assemblages from the sea ice, the highest oc­ currence was displayed by Nitzschia curta, N. cylindrus and N. neglecta. In phy­ toplankton assemblages the highest occurrence was shown by Nitzschia curia, Actinocyclus actinochilus, Chaetoceros criophilum, Corethron criophilum, Thalas­ siothrix antarctica and Nitzschia cylindrus. In the dendrogram of similarities of species composition, two groups of stations were distinguished. The first one was composed of the phytoplankton stations and the second one was composed of the sea ice stations. Microautoradiographic analysis revealed photosynthesis in diatoms from plankton and no photosynthesis in diatoms from brash ice after ice melting. Therefore, the sea ice diatoms could not be regarded as an inoculum for the phytoplankton diatoms in the area studied.
Context-Dependent Attractor Dynamics in Visual Cortex

a. Department of Basic Neuroscience, University of Geneva. CMU, 1 rue Michel Servet, 1211 Genève, Switzerland. b. JST PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan. c. EIIRIS, Toyohashi University of Technology. 1-1 Hibarigaoka, Tempaku, Toyohashi Aichi, 441-8580, Japan. d. Graduate School of Information Science and Technology, the University of Tokyo. 7-3-1 Hongo, Bunkyo, Tokyo 113-8656, Japan. e. Department of Information and Physical Sciences, Graduate School of Information Science and Technology, Osaka University. 1-5 Yamada-oka, Suita, Osaka 565-0871, Japan. f. Institute of Industrial Science, the University of Tokyo. 4-6-1 Komaba, Meguro, Tokyo 153-8505, Japan. g. National Institute for Physiological Sciences. 38 Nishigonaka Myodaiji, Okazaki, Aichi, 444-8585, Japan.
Black-Scholes for scientific computing students

Mathematical finance provides a modern, attractive source of examples and case studies for scientific computing classes. In this installment of education, the author shows how educators can use the Nobel Prize-winning Black-Scholes option valuation theory to motivate exercises in Monte Carlo simulation, matrix computation, and numerical methods for partial differential equations (PDEs).
Changes in protein function underlies the disease spectrum in patients with CHIP mutations

Monogenetic disorders that cause cerebellar ataxia are characterized by defects in gait and atrophy of the cerebellum; however, patients often suffer from a spectrum of disease, complicating treatment options. Spinocerebellar ataxia is caused a encodes the CHIP (C-terminus of HSC70-interacting The spectrum
Modelling of the annual mean maximum urban heat island with the application of 2 and 3D surface parameters

The primary aim of this study was to reveal quantitatively what effect urban structure has on the development, magnitude and spatial distribution of the annual mean maximum urban heat island using a selected representative sample area in Szeged, Hungary. In order to quantify what effect urban structure has on the development of the mean urban heat island a relatively new surface parameter (weighted volumetric compactness) was used that characterises the volume, structure and thermodynamical role of buildings. This new parameter was used in conjucntion with other established surface parameters. How the new parameter and other surface parameters can pinpoint the magnitude and structure of the heat island was investigated. The compactness of approximately 11 000 buildings in onethird of the town was determined by geoinformatical analysis. A stepwise multiple linear regression model was used to determine to what extent each parameter adds to the annual mean urban heat island intensity. According to the results presented here, the connection between compactness and the annual mean (‘all weather’) heat island intensity is stronger than with the sky view factor. Using this modelequation, the absolute deviations of the generated heat island (calculated for an independent 1 yr period) remained under 0.5°C throughout almost the entire investigated area of Szeged. The structure of the estimated heat island with its characteristic features showed clear similarities to the real conditions.
Prevalence and Impact of Malnutrition in Hospitalizations Among Celiac Diseases: A Nationwide Analysis

Background/Aims: Celiac disease (CD) is a T-cell-mediated gluten sensitivity that results in villous atrophy in the small intestine, leading to chronic malabsorption. Patients with celiac disease are prone to malnutrition. We assessed the impact of malnutrition on in-hospital outcomes in patients with CD. Materials and methods: Patients with a primary discharge diagnosis of CD between January 2016 and December 2019 were included in the National Inpatient Sample Database. Data were collected on patient demographics, hospital characteristics, the Charlson Comorbidity Index (CCI), and concomitant comorbidities. The association between malnutrition and outcomes, including mortality, deep vein thrombosis (DVT), pulmonary embolism (PE), sepsis, acute kidney injury (AKI), length of stay (LOS), and total hospitalization charges (THC), was analyzed using the multivariate regression model. Results: A total of 187310 patients with CD were included in the analysis. Patients with CD and malnutrition had a higher risk of mortality (adjusted odds ratio [aOR], 2.08; p<0.001), AKI (aOR=1.18, p=0.003), and DVT (aOR=1.53; p<0.001) compared to patients with CD without malnutrition. No significant difference was noted in the rates of sepsis and PE. Patients with malnutrition also had a prolonged LOS (2.89 days; p<0.001) and higher THC ($22252.18; p<0.001) compared to patients without malnutrition. Discussion: Patients with CD and malnutrition are at high risk of worse outcomes. Early identification of malnutrition in CD can help prevent morbidity and mortality. Even strict adherence to a gluten-free diet has been associated with malnutrition. Further studies identifying factors associated with malnutrition in CD and the impact of interventions to prevent and treat malnutrition are encouraged.