Miracle-dz/UniFAR-FTUs huggingface dataset:
An online sparse estimation-based classification approach for real-time monitoring in advanced manufacturing processes from heterogeneous sensor data

ABSTRACT The objective of this work is to realize real-time monitoring of process conditions in advanced manufacturing using multiple heterogeneous sensor signals. To achieve this objective we propose an approach invoking the concept of sparse estimation called online sparse estimation-based classification (OSEC). The novelty of the OSEC approach is in representing data from sensor signals as an underdetermined linear system of equations and subsequently solving the underdetermined linear system using a newly developed greedy Bayesian estimation method. We apply the OSEC approach to two advanced manufacturing scenarios, namely, a fused filament fabrication additive manufacturing process and an ultraprecision semiconductor chemical–mechanical planarization process. Using the proposed OSEC approach, process drifts are detected and classified with higher accuracy compared with popular machine learning techniques. Process drifts were detected and classified with a fidelity approaching 90% (F-score) using OSEC. In comparison, conventional signal analysis techniques—e.g., neural networks, support vector machines, quadratic discriminant analysis, naïve Bayes—were evaluated with F-score in the range of 40% to 70%.
Scaling Relations for Early‐Type (Red‐Sequence) Galaxies in the Virgo and Fornax Clusters

The photometric and structural properties of early‐type galaxies are examined using HST data from the ACS Virgo and Fornax Cluster Surveys. We show that these galaxies define the local “red sequence” in these two benchmark clusters. Sersic models provide accurate representations of their surface brightness profiles on scales greater than a few percent of the effective radius. On smaller scales, the brightness profiles of bright (MB≳−20.5) galaxies show central deficits with respect to the inward extrapolation of the Sersic models; fainter galaxies often show central excesses (i.e., central stellar nuclei). Aside from these central deviations (which have no effect on the large‐scale galaxy properties), there are gradual and systematic variations in the global photometric and structural parameters along the red sequence luminosity function. A small number of “compact ellipticals” that depart from the relations defined by the majority of red sequence galaxies have likely had their internal structure modified.
An Exploit Traffic Detection Method Based on Reverse Shell

As the most crucial link in the network kill chain, exploiting a vulnerability is viewed as one of the most popular attack vectors to get the control authority of the system, which is dangerous for legal users. Therefore, an effective exploit traffic detection method is urgent. However, current methods are almost based on pattern matching, invalid for encrypted traffic. To address this problem, we propose a reverse shell-based exploit traffic detection method, ETDetector. Our key insight is that the reverse shell attack often coexists with vulnerability exploitation as one of the most popular exploit behaviors. So, we first extract the fusion information feature from original features, such as the packet delay sequence, as input of a decision tree model to identify reverse shell traffic in the shellcode execution stage. Then, we trace suspicious traffic in the shellcode delivery stage by reconstructing the session relationship of the two stages above. Compared with Blatta, using a cyclic neural network to detect early exploit traffic, the detection rate of ETDetector is increased by 50% and valid for encrypted exploit traffic. In addition, we propose a traffic stratification method based on a bisecting K-means algorithm, which can intuitively show the traffic communication behavior and improve the interpretability of ETDetector.
Bidirectional recurrent learning of inverse dynamic models for robots with elastic joints: a real-time real-world implementation

Collaborative robots, or cobots, are designed to work alongside humans and to alleviate their physical burdens, such as lifting heavy objects or performing tedious tasks. Ensuring the safety of human–robot interaction (HRI) is paramount for effective collaboration. To achieve this, it is essential to have a reliable dynamic model of the cobot that enables the implementation of torque control strategies. These strategies aim to achieve accurate motion while minimizing the amount of torque exerted by the robot. However, modeling the complex non-linear dynamics of cobots with elastic actuators poses a challenge for traditional analytical modeling techniques. Instead, cobot dynamic modeling needs to be learned through data-driven approaches, rather than analytical equation-driven modeling. In this study, we propose and evaluate three machine learning (ML) approaches based on bidirectional recurrent neural networks (BRNNs) for learning the inverse dynamic model of a cobot equipped with elastic actuators. We also provide our ML approaches with a representative training dataset of the cobot's joint positions, velocities, and corresponding torque values. The first ML approach uses a non-parametric configuration, while the other two implement semi-parametric configurations. All three ML approaches outperform the rigid-bodied dynamic model provided by the cobot's manufacturer in terms of torque precision while maintaining their generalization capabilities and real-time operation due to the optimized sample dataset size and network dimensions. Despite the similarity in torque estimation of these three configurations, the non-parametric configuration was specifically designed for worst-case scenarios where the robot dynamics are completely unknown. Finally, we validate the applicability of our ML approaches by integrating the worst-case non-parametric configuration as a controller within a feedforward loop. We verify the accuracy of the learned inverse dynamic model by comparing it to the actual cobot performance. Our non-parametric architecture outperforms the robot's default factory position controller in terms of accuracy.
A 15-Year Retrospective Study of Supportive Extracorporeal Therapies Including Plasma Exchange and Continuous Venovenous Hemodiafiltration of 114 Adults with Acute Liver Failure Awaiting Liver Transplantation

Background Recently, there has been a recommendation to utilize a combination of supportive extracorporeal therapies, specifically plasma exchange and continuous venovenous hemodiafiltration, in patients with acute liver failure. This 15-year retrospective study aimed to evaluate supportive extracorporeal therapy, including plasma exchange and continuous venovenous hemodiafiltration, for 114 adults with acute liver failure awaiting liver transplant. Material/Methods In this retrospective study, the medical records of 1288 adult patients who underwent liver transplantation and 161 adult patients who received alternative therapy were analyzed; 114 patients who received combined supportive extracorporeal therapy for acute liver failure were included in the study. Biochemical laboratory data were compared before and after therapy. Results The study included 50 male and 64 female patients. The first group (34 patients) recovered with liver transplantation, and 4 patients died in the first year after liver transplantation. In the second group (80 patients), 66 patients recovered without liver transplantation, while 14 patients died within the first 2 weeks after therapy. All patients showed significant reductions in serum hepatic function tests (alanine transaminase, aspartate transaminase, and total bilirubin), ammonia, and prothrombin time/international normalized ratio after discontinuation of combined supportive extracorporeal therapy (P<0.01). There was also a significant improvement in the hemodynamic parameter. Conclusions This combined extracorporeal therapy can be used as a supportive treatment for both recovery and bridge to liver transplantation in patients with acute liver failure. In addition, treatment can be continued until liver regeneration and until a usable donor is found.
Incorporating Industrial By-Products into Geopolymer Mortar: Effects on Strength and Durability

In recent years, the reuse of industrial waste has become increasingly important for sustainable development. Therefore, this study investigated the application of granulated blast furnace slag (GBFS) as a cementitious replacement material in fly-ash-based geopolymer mortar containing silica fume (GMS). The performance changes in the GMS samples manufactured with different GBFS ratios (0–50 wt%) and alkaline activators were evaluated. The results indicated that GBFS replacement from 0 wt% to 50 wt% significantly affects GMS performance, including improving the bulk density from 2235 kg/m3 to 2324 kg/m3, flexural-compressive strength from 5.83 MPa to 7.29 MPa and 63.5 MPa to 80.2 MPa, respectively; a decrease in water absorption and chloride penetration, and an improvement in the corrosion resistance of GMS samples. The GMS mixture containing 50 wt% GBFS demonstrated the best performances with notable results regarding strength and durability. Owing to the increased production of C-S-H gel, the microstructure of the GMS sample containing more GBFS was denser, as obtained via the scanning electron micrograph analysis results. Incorporating the three industrial by-products into geopolymer mortars was verified when all samples were determined to be in accordance with the relevant Vietnamese standards. The results demonstrate a promising method to manufacture geopolymer mortars that aid sustainable development.
Unrestricted Ketogenic Diet Feeding Enhances Epithelial Ovarian Cancer Growth In Vivo

The ketogenic diet (KD) is hypothesized to impact tumor progression by altering tumor metabolism. In this study, we assessed the impact of an unrestricted KD on epithelial ovarian cancer (EOC) tumor growth, gene expression, and metabolite concentration in a mouse model. ID8 EOC cells, which were syngeneic with C57Bl/6J mouse strain and transfected with luciferase (ID8-luc), were injectedand monitored for tumor development. Female mice were fed either a strict KD, a high fat/low carbohydrate (HF/LC) diet, or a low fat/high carbohydrate (LF/HC) diet (n = 10 mice per group) ad libitum. EOC tumor growth was monitored weekly, and tumor burden was determined based on luciferase fluorescence (photons/second). At the endpoint (42 days), tumors were collected and processed for RNA sequencing. Plasma and tumor metabolites were evaluated using LC-MS. The KD-fed mice exhibited a statistically significant increase in tumor progression in comparison to the HF/LC- and LF/HC-fed groups (9.1 vs. 2.0 vs. 3.1-fold, respectively, p < 0.001). The EOC tumors of the KD-fed mice exhibited significant enrichment of the peroxisome proliferator-activated receptor (PPAR) signaling and fatty acid metabolism pathways based on the RNA sequencing analysis when compared to the LF/HC- and HF/LC-fed mice. Thus, unrestricted KD diet enhanced tumor progression in our mouse EOC model. KD was associated with the upregulation of fatty acid metabolism and regulation pathways, as well as enrichment of fatty acid and glutamine metabolites.
Consumo de jugo de granada (Punica granatum) y su efecto sobre la glucemia, perfil lipídico e histología del páncreas en un modelo de hiperglucemia inducida mediante estreptozotocina

Diversos compuestos bioactivos de los alimentos se han empleado en el tratamiento alterativo de la diabetes mellitus. El jugo de granada posee un alto contenido en compuestos fenólicos a los cuales se les atribuyen propiedades biológicas como hipolipemiante, hipoglucemiante y protector del tejido pancreático. El objetivo de este estudio fue evaluar el efecto del libre acceso de jugo de granada sobre los niveles de glucosa, colesterol, triglicéridos e integridad del tejido pancreático in vivo. Se emplearon 18 ratas macho Wistar inducidas a hiperglucemia con 60 mg estreptozotocina/kg de peso corporal intraperitoneal (IP). Se formaron tres grupos experimentales. El grupo HS expuesto a solución de sacarosa, el grupo HJG expuesto a jugo de granada y el grupo HSI expuesto a solución de sacarosa y tratamiento con insulina. Los resultados mostraron que, las ratas del grupo HJG consumieron jugo de granada durante 21 días, lo que resultó en la reducción de los niveles de glucosa con respecto a su valor inicial de 417 a 356 mg/dL, no de manera significativa (p>0.05). Los niveles de lípidos mostraron una reducción no significativa al finalizar la intervención (p>0.05). El estudio histológico del páncreas en el grupo HJG mostró conservación de la arquitectura pancreática y presencia de islotes de Langerhans; mientras que el grupo HS mostró extensa necrosis pancreática y el grupo HSI mostró daño intermedio con escasos islotes de Langerhans. Se sugiere que el jugo de granada posee efectos hipoglucemiantes y protege el tejido pancreático en ratas hiperglucémicas inducidas.
Dielectric Spectroscopy Studies and Modelling of Piezoelectric Properties of Multiferroic Ceramics

Compounds and solid solutions of bismuth ferrite (BiFeO3)—barium titanate (BaTiO3) system are of great scientific and engineering interest as multiferroic and potential high-temperature lead-free piezoelectric materials. In the present paper, the results of research on the synthesis and characterisation of 0.67Bi1. 02FeO3–0.33BaTiO3 (67BFBT) ceramics in terms of crystal structure and dielectric and piezoelectric properties are reported. It was found that the produced 67BFBT ceramics were characterised by a tetragonal crystal structure described by the P4mm space group, an average crystallite size ≈ 80 nm, and an average strain = 0.01%. Broad-band dielectric spectroscopy (BBDS) was employed to characterise the dielectric response of polycrystalline ceramics. The frequency range from ν = 10−1 Hz to ν = 105 Hz was used to characterise the influence of the electric field strength on dielectric response of the ceramic sample at room temperature. The dielectric spectra were checked for consistency with the Kramers–Kronig test, and the high quality of the measurements were confirmed. The electric equivalent circuit method was used to fit the dielectric spectra within the frequency range that corresponded to the occurrence of the resonant spectra of the radial mode for thin disk sample, i.e., from ν = 105 Hz to ν = 107 Hz and the temperature range from T = −20 °C to T = 50 °C. The electric equivalent circuit [RsCPE1([L1R1C1]C0)] was used, and good fitting quality was reached. The relevant calculations were performed, and it was found that the piezoelectric charge coefficient exhibited a value of d31 = 35 pC/N and the planar coupling factor was kp = 31% at room temperature. Analysis of impedance spectra performed in terms of circumferential magnetic field made it possible to establish an influence of magnetic field on piezoelectric parameters of 67BFBT multiferroic ceramics. Additionally, the “magnetic” tunability of the modulus of the complex dielectric permittivity makes 67BFBT a sensing material with vast potential.
Types of political connections, election years, and firm performance in Pakistan: Moderating role of external monitoring

Abstract The study aims to examine the impact of different types of political connections in Pakistan on the performance of firms. We further examine whether the presence of external monitors, such as foreign and institutional investors, can moderate the impact of political connections on the performance of firms in Pakistan. In addition, we explore the association between political connections and firm performance during election and non-election years. This study uses 2479 firm-year observations for firms listed on the Stock Exchange of Pakistan from 2010 to 2019 as the final sample and uses regression to test the hypotheses. The findings of this study show that political connections are negative and strongly significant across all three performance indicators, such as ROA, ROE, and Tobin’s Q, indicating that political connections can harm firm value. Further analyses indicate that the detrimental impact of political connections on firm performance is attributable to CEOs who have political connections and is more pronounced during general election years in Pakistan. The findings further report some weak evidence of the monitoring roles played by foreign and institutional in mitigating the negative impact of political connections. Policymakers in Pakistan, therefore, ought to design stricter disclosure measures to limit the potential wealth expropriation in politically connected firms, given the lack of shareholder activism by outside shareholders in this country. Our results further suggest that external monitors, such as foreign and institutional ownership, play a relatively limited role in mitigating the adverse impact of political connections on the performance of firms.
A comparison of diffusion MRI presurgical tractography techniques with intraoperative mapping-based validation

Objectives Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This work investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)-based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. Material and methods Five different tractography methods were compared (3 DTI-based and 2 CSD-based) in 22 preoperative neurosurgical patients. The corticospinal tract (CST, N=20) and arcuate fasciculus (AF, N=7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver-operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. Results Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD-based compared to DTI-based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD-based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE < 0.05). Conclusion CSD-based CST tractograms were more accurate than DTI-based ones when validated using DES-based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice. Clinical relevance statement CSD-based tractograms of the CST are more sensitive than DTI-based tractograms when validated against sensory-motor DES mapping. This also demonstrated the feasibility of fully-automated CSD-based tractography for presurgical planning of the CST.
Global Longitudinal Active Strain Energy Density (GLASED): A Powerful Prognostic Marker in a Community-Based Cohort

BACKGROUND Identifying the imaging methods that best predict heart failure risk, cardiovascular adverse events and death is crucial for tailoring optimal management. Potential prognostic markers include myocardial mass, left ventricular ejection fraction, myocardial strain, stroke work, contraction fraction, pressure-strain product and a new measurement called global active longitudinal strain density (GLASED). OBJECTIVES This study sought to assess the utility of a range of potential prognostic markers of left ventricular structure and contractile function in a community-based cohort. METHODS The impact of cardiovascular magnetic resonance image-derived markers, extracted by machine learning algorithms were compared to the future risk of adverse events in a group of 44,957 UK Biobank participants. RESULTS Most markers, including the left ventricular ejection fraction, had limited prognostic value. GLASED was significantly associated with heart failure, all-cause mortality and major adverse cardiovascular events with hazard ratios of approximately 1.4. CONCLUSIONS GLASED predicted major cardiovascular adverse events and mortality with the highest hazard ratios compared with conventional markers. The routine use of GLASED is recommended for assessing prognosis.
Proton beam therapy for gliomas: a multicenter prospective registry study from all proton beam facilities in Japan

Abstract We reviewed the outcomes of glioma patients enrolled in a prospective observational registry study of proton beam therapy (PBT) in Japan. The inclusion criteria were glioma patients registered in the Electronic Data Capture system, the Proton-net, between May 2016 and July 2019. Data on patient characteristics, treatments, late adverse events, survival status, recurrence and secondary tumors were extracted and statistically analyzed. The primary endpoint was the overall survival (OS) rate, and the secondary endpoints were the progression-free survival (PFS) rate and cumulative local recurrence rate (cLRR). Of the 65 primary brain tumor patients registered, 29 glioma patients from eight of 19 PBT facilities met the inclusion criteria. There were 19 glioblastoma patients, eight of other malignant gliomas, and two of low-grade gliomas. For glioblastomas, with a median follow-up period of 16 months, the median survival time was 21.2 months and the OS at 1, 2, 3 and 4 years were 77.4%, 44.9%, 23.9% and 23.9%, respectively. The median PFS period was 10.1 months, the 1, 2, 3 and 4-year PFS were 32.4%, 19.4%, 9.7% and 9.7%, respectively. The 1, 2, 3 and 4-year cLRR were 56.1%, 68.8%, 78.4 and 78.4%, respectively. Grade 3 brain necrosis was observed in two patients. No secondary tumor was observed. This is the first report on the current status of PBT for gliomas in Japan. For glioblastomas, the outcomes of PBT are estimated to be equivalent to historical data of photon therapy. The results of a prospective comparative evaluation of PBT and photon therapy are awaited.
Safety and Accuracy of Professional Continuous Glucose Monitoring in Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplantation

Hyperglycemia in the early days following allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a well-known risk factor for acute graft-versus-host disease (GVHD) and non-relapse mortality. The FreeStyle Libre Pro, a factory calibrated continuous glucose monitoring (CGM) device, has been used for the retrospective analysis of glucose testing in patients with diabetes. We assessed the safety and accuracy of the device in patients undergoing allo-HSCT. We recruited eight patients who underwent allo-HSCT between August 2017 and March 2020. They wore the FreeStyle Libre Pro on the day before or on the day of transplantation until 28 days after transplantation. Adverse events, especially bleeding and infection, were monitored to assess safety, and blood glucose levels were measured and compared with the device values. None of the eight participants experienced bleeding that was difficult to stop from the sensor site or local infection that required antimicrobial administration. The device value was well correlated with blood glucose (correlation coefficient r=0.795, P<0.01); however, the overall mean absolute relative difference was 32.1%±16.0%. Our study demonstrated the safety of FreeStyle Libre Pro in allo-HSCT patients. However, the sensor results tended to be lower than the blood glucose levels.