Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic resistance in pancreatic ductal adenocarcinoma: Current challenges and future opportunities

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the United States. Although chemotherapeutic regimens such as gemcitabine+ nab-paclitaxel and FOLFIRINOX (FOLinic acid, 5-Fluroruracil, IRINotecan, and Oxaliplatin) significantly improve patient survival, the prevalence of therapy resistance remains a major roadblock in the success of these agents. This review discusses the molecular mechanisms that play a crucial role in PDAC therapy resistance and how a better understanding of these mechanisms has shaped clinical trials for pancreatic cancer chemotherapy. Specifically, we have discussed the metabolic alterations and DNA repair mechanisms observed in PDAC and current approaches in targeting these mechanisms. Our discussion also includes the lessons learned following the failure of immunotherapy in PDAC and current approaches underway to improve tumor’s immunological response.
Sequential Estimation of the Radial Temperature Variation in Overhead Power Cables

Abstract Cables used in electric power transmission lines are usually composed of layers of stranded metallic wires. Several effects cause a nonuniform distribution of the electric current, which significantly influences heat generation within the cable. The accurate prediction of the cable radial temperature variation is thus of great importance for the design and operation of electric power transmission lines, because of economic and safety reasons. In this work, the Particle Filter method is applied to estimate the transient temperature distribution in the cross section of an Aluminum Conductor Steel Reinforced power cable, by using measurements of the cable surface temperature obtained with an infrared camera. The Sampling Importance Resampling (SIR) algorithm of the Particle Filter method is used for the solution of the state estimation problem, by taking into account uncertainties in the evolution heat conduction model within the cable, as well as in the measured temperatures. The results presented in this work reveal an excellent agreement of the estimated temperatures obtained with the SIR algorithm and temperature measurements from thermocouples inserted into the cable during the manufacturing process, thus validating the proposed approach for the estimation of the radial temperature variation in the power cable.
The oral KIF11 inhibitor 4SC‐205 exhibits antitumor activity and potentiates standard and targeted therapies in primary and metastatic neuroblastoma models

Dear Editor, Neuroblastoma remains incurable for most patients with high-risk disease.1 Perturbation of transcription factors (MYCN and PHOX2B), kinases (ALK, MEK), and cell cycle regulators (CDK4/6, CHECK1), among other factors, make neuroblastoma cells highly proliferative, which is associated with poor patient outcomes.2,3 To circumvent the limitations of the classical microtubule poisons such as vinca alcaloyds used in the treatment of neuroblastoma,1 we sought to explore alternative mitotic regulators as new therapeutic targets for high-risk neuroblastoma patients. One of these mitotic spindle-specific proteins is kinesin family member 11 (KIF11), also known as kinesin spindle protein, kinesin-5, or Eg5, which is essential for bipolar spindle formation andmitotic progression inhuman cells.4 Transcriptomic analyses showed that the expression of multiple kinesins, including KIF11 was higher in the highrisk neuroblastoma compared with lowand intermediaterisk groups (Figures 1A and S1; Table S1). Overall survival was significantly poorer in patients with high KIF11 expression (Figure 1B–D; Table S2). KIF11 high expression was identified as an independent prognostic factor of survival, together with risk assessment (HR= 3.051; Table S3) and found to be higher in patients with amplification of MYCN, 1p36 loss, or 17q23 gain (Figure 1E). At the protein level, KIF11 expression was detected in the cytoplasm of neuroblastic cells (Figure 1F) and showed higher expression compared to lowor intermediate-risk neuroblastoma samples (p < 0.05) and in tumors with segmental chromosome alterations such as 1p36, 11q deletion, and gain of 17q23 (Table S4). Kaplan–Meier analysis confirmed that high KIF11 protein expression was associated with shorter event-free and overall survival (Figures 1G and H). While there is a positive correlation between KIF11 and MYCN mRNA expression levels, MYCN is neither sufficient, nor necessary for KIF11 expression (Figure S2).
Design and Control of Drones

The design and control of drones remain areas of active research, and here we review recent progress in this field. In this article, we discuss the design objectives and related physical scaling laws, focusing on energy consumption, agility and speed, and survivability and robustness. We divide the control of such vehicles into low-level stabilization and higher-level planning such as motion planning, and we argue that a highly relevant problem is the integration of sensing with control and planning. Lastly, we describe some vehicle morphologies and the trade-offs that they represent. We specifically compare multicopters with winged designs and consider the effects of multivehicle teams. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
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— This study aims to analyze the impact of industry 4.0 on the healthcare system. Scopus database is used to extract the data, and 297 articles are initially found in the database. We used the PRISMA statement 2015 to include and exclude data; the final 48 articles were included for the review. The author’s keyword and VOS viewer co-occurrence of the terms are classifying the same result. The records are presented in three major categories, and outcomes are discussed accordingly in the classification of literature. Healthcare systems, cloud computing digital technologies are the major research areas in industry 4.0 in the last decade. Healthcare is significantly improved due to the technolo - gies and services influenced by industry 4.0. The findings of the study showing that industry 4.0 is enhancing standards of healthcare significantly. Industry 4.0 enables many new technologies, like blockchain, big data, cloud computing, and IoTs, to track patients’ medical records. That more accessible for healthcare professionals to understand the patient’s history and deal accordingly.
Association Between Levels of Urine Di-(2-ethylhexyl)phthalate Exposure, a Potentially Harmful and Invisible Chemical, and Heart Rate Variability in Young Adults

BackgroundPhthalate exposure is associated with cardiovascular risk. Among the various phthalates, di-(2-ethylhexyl) phthalate (DEHP) is the most important plasticizer in our daily lives. This study investigated the association between DEHP exposure and the alteration of heart rate variability (HRV). MethodsDuring 2017-2019, we recruited 974 young adults to investigate the effects of living environments and dietary habits on cardiometabolic disorders in Taiwan. We quantitatively analyzed urinary metabolites of phthalates, including mono-(2-ethylhexyl) phthalate (MEHP), mono-(ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP). A continuous electrocardiogram was recorded to obtain a 5-minute ECG. Time-domain and frequency-domain HRV analyses were performed.ResultsMultiple linear regression showed that urinary oxidized DEHP metabolites MEHHP and MEOHP were associated with decreased HRV after controlling for associated cardiovascular risk factors. A higher MEHHP level was associated with a lower TINN (triangular interpolation of NN interval histogram), very-low-frequency (VLF), and low frequency/high frequency (LF/HF) ratio. A higher MEOHP level was associated with a decreased LF/HF ratio. In addition, trend analysis showed that higher MEHHP and MEOHP quantiles were significantly associated with a decreased LF/HF ratio.Conclusions﻿DEHP is a potentially harmful and invisible chemicals. The urinary DEHP metabolites MEHHP and MEOHP are associated with decreased HRV, indicating an unfavorable autonomic balance in young adults in Taiwan.
The Pupillary Light Reflex as a Biomarker of Concussion

The size of our pupils changes continuously in response to variations in ambient light levels, a process known as the pupillary light reflex (PLR). The PLR is not a simple reflex as its function is modulated by cognitive brain function and any long-term changes in brain function secondary to injury should cause a change in the parameters of the PLR. We performed a retrospective clinical review of the PLR of our patients using the BrightLamp Reflex iPhone app. The PLR variables of latency, maximum pupil diameter (MaxPD), minimum pupil diameter (MinPD), maximum constriction velocity (MCV), and the 75% recovery time (75% PRT) were associated with significant differences between subjects who had suffered a concussion and those that had not. There were also significant differences in PLR metrics over the life span and between genders and those subjects with and without symptoms. The differences in PLR metrics are modulated not only by concussion history but also by gender and whether or not the person has symptoms associated with a head injury. A concussive injury to the brain is associated with changes in the PLR that persist over the life span, representing biomarkers that might be used in clinical diagnosis, treatment, and decision making.
Chemical features of rejected taro tuber flour (Colocasia esculenta L. Schott) and its effect on productive performance in post-weaning pigs

This study evaluated the effect of the inclusion of rejected taro tuber flour (RTTF) on the productive performance in commercial hybrid pigs (Landrace × Duroc × Pietrain) during their post-weaning period. The experiment was established under a completely randomized design, comprising four treatments (0, 10, 20, and 30% inclusion of RTTF in the diet), using a total of 60 piglets with 15 repetitions each. The average daily feed intake (ADFI), average daily gain (ADG), feed conversion (FC), final body weight (BW), presence of diarrheas, mortality, and production cost, were determined. RTTF showed a high dry matter content, nitrogen-free extracts, gross energy, aspartic acid, glutamic acid, potassium, iron, polyphenols, and antioxidant activity. RTTF inclusion in the diet of pigs in the entire period (30-58 d) did not cause diarrhea or deaths and showed a quadratic effect on BW (p < 0.001) and ADFI (p < 0.001) and produced a linear effect on ADG (p = 0.006), FC (p = 0.003) and production cost (p < 0.001). In conclusion, the inclusion of RTTF in the diet of pigs after weaning (30-58 d) ranging between 0 and 30 % showed no effect on BW and ADFI, with a slight decrease in ADG and FC and a linear effect on production cost reduction.
The Traffic Management Intrusion and Compliance System as Security Situation Assessment System at an Air Traffic Controller's Working Position

The need to protect air traffic control against attacks and detect security incidents is widely accepted. Nevertheless, depending on the systems and procedures, it is sometimes difficult to distinguish whether "something is not as it should be". On the one hand, it could be due to a failure, on the other, it could be because of an intentional interruption/abuse. This paper lists five specific kinds of indications that may be found analyzing the traffic situation and the radio communication at a controller working position and details how they are detected. Those indications are non-conformant movements, conflicts, unusual clearances/behavior, unauthorized speakers and detected stress. Furthermore, a correlation function is described which determines the security situation indicator. This indicator categorizes the security situation into three different states expressing how likely it is that the detected indications may represent a security situation needi ng attention: “green”, meaning there are no security - related actions needed; “yellow”, meaning something seems strange, be aware; and “red”, meaning that there is most properly a security incident. The Traffic Management Intrusion and Compliance System (TraMICS) is supposed to assist as well the air traffic controllers and the operators in a security operation center by being part of an airport security architecture.
The resistance and short‐term resilience of a restored extracted peatland ecosystems post‐fire: an opportunistic study after a wildfire

Bogs are known to be relatively resistant and resilient to fire, due to the dominance of wet Sphagnum mosses. Indeed, Sphagnum mosses by holding water, ensure bog resistance, and by regenerating from any fragments left post‐fire, ensure bog resilience. The return of several ecological attributes has been reported in the literature post‐restoration. However, the resistance and resilience have not yet been evaluated in restored peatlands. A fire affecting an extracted peatland restored 10 years ago provided the opportunity to (1) evaluate the losses post‐fire, in terms of phytobiomass and plant cover and (2) assess early vegetation recovery after one growing season post‐fire. The fire response of the restored peatland, in terms of resistance and short‐term resilience, differed between the main plant communities. Sphagnum Lawn communities (Sphagnum species from the Acutifolia subgenus and Eriophorum vaginatum) showed greater resistance to fire losing proportionally less phytobiomass (17%) than Wet Hollow communities (44%) (Sphagnum species from the Cuspidata subgenus and Scirpus cyperinus). Greater resistance of the Sphagnum Lawn likely comes from the Acutifolia Sphagnum species growing in dense carpets with good water retention, along with the E. vaginatum tussocks being able to retain humidity below the tussocks, whereas the looser growth habit of Cuspidata Sphagnum species do not have good capillary rise capacity and Scirpus produced litter that can produce a good fuel. This study reinforces the idea that a peatland restoration approach using reintroduction material dominated by Acutifolia Sphagnum species and tussock cottongrass provides a better resistance and short‐term resilience of restored peatlands.
A Square-Root Factor-Based Multi-Population Extension of the Mortality Laws

In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.
Exports and firm employment: the roles of R&D and exports to affiliates

ABSTRACT Firm-level data from the Korean manufacturing sector is used to quantify the impact of both the extensive and intensive margins of exporting on employment, emphasizing the role of both firm-level R&D intensity and exports to foreign affiliates. The employment effects of exporting by employment contract status, i.e. regular or non-regular employees, are also separately examined. Here, findings show that a firm’s entry into export markets has a positive effect on its employment of regular workers; further, this positive effect is apparent in firms that belong to the group with the highest level of R&D intensity. With regard to the intensive margin, findings show that the negative impact on regular employment of firms’ export share in total sales stands out in the case of exports to non-affiliates. This negative impact, related to the intensive margin, is apparent in firms belonging to the group with the lowest R&D intensity, which is in line with the results for the extensive margin. The heterogeneous effects of exports depending on both firm-level R&D intensity and exports to foreign affiliates seem to be associated with the uncertainty that is due to the volatility of overseas sales.
Determination of Quinolones in Human Urine and Water Samples by Ultrasound Assisted Dispersive Liquid-Liquid Microextraction Based on Solidification of Floating Organic Droplet Followed High Performance Liquid Chromatography

Quinolones (QNs) are the most important class of synthetic antibiotics in human and veterinary medicines. They are effective to control a wide range of bacteria, both gram positive and negative as well as other bacteria and often used in the treatment of a range of illnesses. Due to the fact that its resistance in the environment can cause undesirable effects on aquatic ecosystems and human health, QNs have obtained growing attention [1,2]. Therefore, the analysis of the occurrence, distribution and risks of quinolone antibiotics became crucial to environment monitoring.
Network Abnormal Traffic Detection Model Based on Semi-Supervised Deep Reinforcement Learning

The rapid development of Internet technology has brought great convenience to our production life, and the ensuing security problems have become increasingly prominent. These problems threaten users’ privacy and pose significant security risks to the normal conduct of many aspects of society, such as politics, economy, culture, and people’s livelihood. The growth of the information transmission rate expands the scope of attacks and provides a more attack environment for intruders. Abnormal detection is an effective security protection technology that can monitor network transmission in real-time, effectively sense external attacks, and provide response decisions for relevant managers. The development of machine learning has also led to the development of abnormal traffic detection technology. The goal has been to use powerful and fast learning algorithms to deal with changing threats and respond in real-time. Most of the current abnormal detection research is based on simulation, using public and well-known datasets. On the one hand, the dataset contains high-dimensional massive data, which traditional machine learning methods cannot be processed. On the other hand, the labeled data scale is far behind the application requirements, and the dataset’s labels are all manually labeled, so the labeling cost is exceptionally high. This paper proposes a semi-supervised Double Deep Q-Network (SSDDQN)-based optimization method for network abnormal traffic detection, mainly based on Double Deep Q-Network (DDQN), a representative of Deep Reinforcement Learning algorithm. In SSDDQN, the current network first adopts the autoencoder to reconstruct the traffic features and then uses a deep neural network as a classifier. The target network first uses the unsupervised learning algorithm K-Means clustering and then uses deep neural network prediction. The experiment uses NSL-KDD and AWID datasets for training and testing and performs a comprehensive comparison with existing machine learning models. The experimental results show that SSDDQN has certain advantages in time complexity and achieved good results in various evaluation metrics.
User-generated videos and tourists’ intention to visit

ABSTRACT In pursuit of better travel decisions, potential tourists are not only exposed to online destination marketing content but are also exposed to user-generated content (UGC) which are based on the subjective evaluation of people's travel experiences. These user-generated contents have been observed to significantly influence tourist travel intentions, vlogs in particular. This paper aims to further our understanding of how tourists perceive user-generated videos and their influence on their travel intentions. A survey was conducted among tourists (n = 274) in Cape Coast Castle, Ghana and analysed using a Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. Results suggest that tourist's perception of user-generated videos in relation to their perceived credibility and perceived fairness influenced their travel intentions.
A Template for the Validation of DART-MS for Qualitative Seized Drugs Analysis

Direct analysis in real time mass spectrometry (DART-MS) is an increasingly employed tool for a wide range of forensic applications including seized drug analysis. A significant body of research surrounds DART-MS for the analysis of seized drugs and how it can be used to address many of the challenges caused by the increased presence of emerging drugs and novel psychoactive substances. A lack of available resources to help address validation, operation, training, and data interpretation needs is just one of the hurdles that laboratories face when adopting new technologies, such as DART-MS. To provide additional resources to assist in validation development, this work provides a template that can be adopted or adapted for DART-MS or other ambient ionization mass spectrometry techniques for qualitative seized drug analysis. The template, which was created as a result of recent implementation efforts, provides a description of validation studies with a focus on understanding the potential challenges and limitations caused by the prevalence of novel psychoactive substances and other emerging drugs. The studies address accuracy and precision, reproducibility, specificity, sensitivity, environmental factors, use in casework, and robustness. In addition to providing a template for validation, the results obtained from completing these studies on two high-resolution DART-MS systems are also presented. This work, and the corresponding supplemental information, was created to add to the available resources that laboratories can leverage to assist in overcoming the adoption hurdles of ambient ionization mass spectrometry methods such as DART-MS.
The Effect of Small Game Exercise on Freestyle Swimming Speed: A Case Study of Halu Oleo University Sport Science Student

The Effect of Small Game Exercise on Speed: A Case Study Abstract Mastering freestyle swimming focuses on increasing the swimming speed in order to complete the swimming distance in the shortest time. Because training for freestyle swimming must be carefully programmed and is progressive-based, this study is set to investigate the effect of small game exercises on freestyle swimming speed among the sport science student of Halu Oleo University. This study uses an experimental method with the one group pretest-posttest design. The population of this study consists of 10 students of Halu Oleo University Sport Science Student taken by simple random sampling. The instruments used were equipment for small games and exercises in the techniques of feet, hands, breath and freestyle swimming coordination. Samples of swimming exercises were speed records with a frequency of 3 times a week and carried out for 6 weeks. The results of the normality and homogeneity test data analysis showed a significance value of p > 0.05, which means that the data were normally distributed and homogeneous. T -test results showed a significance value of p > 0.05 with a calculated F value of 63.119 and an F table of 5.296, it can be concluded that there was a significant effect of small game training on the freestyle swimming speed for Sport Science Student of Halu Oleo University.