Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of open-source image analysis tools for mammalian cell culture: algorithms, features and implementations

Cell culture is undeniably important for multiple scientific applications, including pharmaceuticals, transplants, and cosmetics. However, cell culture involves multiple manual steps, such as regularly analyzing cell images for their health and morphology. Computer scientists have developed algorithms to automate cell imaging analysis, but they are not widely adopted by biologists, especially those lacking an interactive platform. To address the issue, we compile and review existing open-source cell image processing tools that provide interactive interfaces for management and prediction tasks. We highlight the prediction tools that can detect, segment, and track different mammalian cell morphologies across various image modalities and present a comparison of algorithms and unique features of these tools, whether they work locally or in the cloud. This would guide non-experts to determine which is best suited for their purposes and, developers to acknowledge what is worth further expansion. In addition, we provide a general discussion on potential implementations of the tools for a more extensive scope, which guides the reader to not restrict them to prediction tasks only. Finally, we conclude the article by stating new considerations for the development of interactive cell imaging tools and suggesting new directions for future research.
Association and Interaction between Heavy Metals and Hyperuricemia in a Taiwanese Population

The prevalence of hyperuricemia in Taiwan is high, and hyperuricemia has been associated with a risk of developing several diseases. Although the traditional risk factors for hyperuricemia are well known, the relationship between heavy metals and hyperuricemia is still undefined. Therefore, the aim of this study was to investigate the relationship between hyperuricemia and heavy metals. A total of 2447 participants (977 males and 1470 females) residing in southern Taiwan were enrolled, and levels of the following heavy metals were measured: lead in blood, and nickel, chromium, manganese, arsenic (As), copper, and cadmium in urine. Hyperuricemia was defined as a serum uric acid level greater than 7.0 mg/dL (416.5 μmol/L) in men and 6.0 mg/dL (357 μmol/L) in women. The participants were divided into two groups: those without hyperuricemia (n = 1821; 74.4%) and those with hyperuricemia (n = 626; 25.6%). Multivariate analysis showed that only high urine As (log per 1 μg/g creatinine; odds ratio, 1.965; 95% confidence interval, 1.449 to 2.664; p < 0.001), young age, male sex, high body mass index, high hemoglobin, high triglycerides, and low estimated glomerular filtration rate were significantly associated with hyperuricemia. In addition, the interactions between Pb × Cd (p = 0.010), Ni × Cu (p = 0.002), and Cr × Cd (p = 0.001) on hyperuricemia were statistically significant. Increasing levels of Pb and Cr yielded an increased prevalence of hyperuricemia, and the effect was progressively greater for increasing Cd. Moreover, increasing levels of Ni yielded an increased prevalence of hyperuricemia, and the effect was progressively greater for increasing Cu. In conclusion, our results show that high urine As is associated with hyperuricemia, and some interactions of heavy metals on hyperuricemia are noted. We also found that young age, male sex, high BMI, high hemoglobin, high triglycerides, and low eGFR were significantly associated with hyperuricemia.
Attack Classification Analysis of IoT Network via Deep Learning Approach

A variety of attacks in the transportation layer of IoT network seeks for a detection and preventionmechanism such as intrusion detection systems (IDSs). Anomaly detection is one of the most demandingtask in IDSs. It requires a robust classifier model which is able to detect different kinds ofattacks intelligently. This paper addresses deep neural network for classifying attacks in IoT network.The performance of the proposed method is evaluated on the three novel benchmarking datasets inwired and wireless network environment, i.e. UNSW-NB15, CIDDS-001, and GPRS. Furthermore,deep neural network combined with grid search strategy are utilized to obtain the best parameter settingsfor each dataset. The experimental results demonstrate the effectiveness of our approach usingdeep neural network in terms of accuracy, precision, recall and false alarm rate.
Research of a logistics coordination level in procurement

This study aims to investigate the level of logistical coordination and the state of coordination mechanisms in procurement activities among enterprises involved in supply chains. The research was conducted through a comparative analysis of statistical data obtained from a survey of businesses between July and October 2021.The study proposes a method for identifying general and individual performance indexes for partner companies' interactions by examining joint planning, synchronized documentation, coordinated operational procedures, and resource integration. This method is relevant to both logistics theory and the practical activities of supply chain participants. The research highlights the evolution of metrics used to evaluate the extent of coordination mechanisms employed by businesses in their procurement activities. Based on the selection criteria, an assessment scale is proposed to determine the level of logistical coordination in supply chain companies' procurement activities. The findings offer insights into the development of coordination mechanisms for organizations across various sectors (industrial, trading, freight forwarding), focusing on their scientific significance and impact on the competitiveness of consolidated supply chains. This study contributes to the literature by providing a comprehensive understanding of logistical coordination and coordination mechanisms in procurement activities among supply chain enterprises, as well as offering a practical assessment scale for evaluating logistical coordination levels.
Estimation of the fundamental matrix based on EV model

This thesis presents a nonlinear method to estimate the fundamental matrix, a key problem arising in projective motion estimation and reconstruction, based on a general Errors-in-Variables (EV) model. In this model, the method considers that all the measurements are corrupted by noises, and minimizes a cost function derived from a nonlinear criterion to estimate both the fundamental matrix and corrupted data, involving the rank-2 constraint With reasonably adjusted data, this method turns out to significantly increase the accuracy and robustness with a simple form of computation. The performance of the proposed approach is justified by theory and assessed by several experiments on real images.
ESTIMATION OF EDSS FROM EEG SIGNALS OF MULTIPLE SCLEROSIS PATIENTS

Multiple sclerosis (MS) is an autoimmune, neurodegenerative, chronic disease that affects the central nervous system and manifests itself with attacks. Although there is no definite cure for the disease, it is possible to control the attacks. Follow-up of the disease has great importance in terms of disability. An Extended Disability Status Scale (EDSS) is used to show how much the disease affects. This score is determined by specialized clinicians. In this study, the EDSS score, previously determined by neurologists, was tried to be estimated using the EEG signals. 32-channel EEG signals were recorded while 17 MS patients with EDSS 1.0, 1.5, and 2.0 were performing the working memory task. Using the band power of these 6-minute EEG signals, EDSS estimation was made with the Decision Tree Regressor with 0.088 Mean Absolute Error (MAE). With Leave One Out Cross-Validation, 17 trees were extracted and 12 were found to be identical. As a result, the band power features of F7 and CP2 EEG channels were found to be successful in 3-level EDSS prediction with decision tree regressor with 0.0 MAE. In addition, the relationship between the scores obtained in the working memory task and the EDSS scores of MS patients was statistically calculated with One-way ANOVA. There was no significant difference between the EDSS score and the task score (p>.05).
A Survey on Detection Methods Against Internet Worm Attacks

Miscellaneous attacks against the Internet have become one of the major concerns among many imperfectionsin contemporary cyberspace. In particular, worms are one highly dangerous type. Howto timely detect and utterly stop such attacks still remains an unresolved issue, and it is of greatnecessity to review the existing quality work in the field of worm detection. In this paper, majorcharacteristics, working mechanisms, and the life cycle of worms are introduced. Then, we divideexisting worm detection techniques into two categories: machine learning methods and traditionaldetection methods, and existing worm countermeasures are reviewed in detail by category. Finally,some open issues in the field of worm detection are discussed, and the contents of this paper aresummarized. The goal of this paper is to let researchers comprehensively understand various existingdefense mechanisms against worms.
Mapping and sensing Dewey's situations as design and social science methods

This exploratory paper proposes the use of pragmatist philosophy as a methodological bridge between design and the social sciences. It develops John Dewey’s ecological notion of the ‘situation’ into two design methods for mapping and sensing situations. The first method, called ‘mapping situations’ is based on Adele Clarke's concept of ‘situational mapping’ and aims to pinpoint actor relations, concealed power dynamics, and areas for intervention. The second method, ‘sensing situations’ helps to develop a deeper understanding of a situation through embodied experience. The combination of these cognitive and affective methods offers a holistic approach to deal with complexity and ambiguity. The potential of these methods is to use Dewey’s situation as a shared unit of analysis that allows designers and social scientists to work together and address problems in new and innovative ways that go beyond the limits of their respective fields.
Exploring the Risk Factors for Rear-End Collisions on Indonesian Toll Roads

Rear-end collisions are the most frequent type of collision on toll roads in some countries. The potential risks of rear-end collisions were drivers, vehicles, roads, and the environment. In Indonesia, rear-end collisions frequently occur on the Jakarta-Bogor-Ciawi (Jagorawi), Cikampek-Purwakarta-Padalarang (Cipularang) and Cikopo-Palimanan (Cipali) toll roads. Few previous studies have focused on risky driving behavior phenomena in Indonesia on rear-end collision risks. This study aims to explore the risks of rear-end collisions on Indonesian toll roads especially risky driving behavior. This study conducted a structured interview with 20 drivers and used voice call WhatsApp application. The results showed that the rank (high-low) of rear-end collision risks based on participants’ perception were driver, road, environment, and vehicle. Data show that 70% of participants choose to increase their speed to overtake the truck when it is directly in front of their vehicle. In other circumstances, 55% of participants drive at the same speed in a situation where the bus is the lead vehicle. It also happened in 90% of participants facing a passenger vehicle as the lead vehicle. In addition, the interview result show Cipali and Cipularang toll road sections have a high risk for rear-end collisions.
3D printed passive end-effector for industrial collaborative robotic arms

The work focuses on the design and prototyping of a novel end-effector for a collaborative robotic arm allowing to grab and drag industrial packages without lifting them. The proposed solution consists of a passive 3D-printed end-effector manufactured using carbon fibre reinforced Onyx material. Thanks to the entirely passive mechanical actuation that exploits the compliance of the main chassis, this end-effector features a simple, scalable, and inexpensive structure. This lightweight end-effector is specifically designed for small and low payload collaborative robotic arms. Specifically, the proposed end-effector includes three main parts. First, a thin blade, with the main function of separating boxes that are close to each other. Second, a rocker arm - rod mechanism, which allows an opposable bracket to be moved in order to grab the correspondent package. This is proportionally and passively actuated by the contact pressure between the package, during its grip, and a paddle (third part), which is composed of a flat leverage and three flexural springs to counterbalance the pushing force. This paddle and the main body of the gripper were designed as a single part exploiting 3D printing manufacturing capabilities. Moreover, we implemented a Simscape dynamic model that predicts the functionality of the end-effector during standard operations. The work shows how to design, develop and validate a new low cost, passive end-effector mainly oriented to collaborative robots. The final prototype demonstrates its entire functionality, and proves fabricability through 3D printing, thus minimizing production costs, weight, and time.
SVM based Traffic Classification for Mitigating HTTP Attack

The advancement in Internet technology brings new dimension to commercial applications, entertainmentand information sharing. Consequently, many web services are launched in almost all needs ofthe internet users. The development of effective network infrastructure increases the usage of theseservices. However the convenience of using the web services are blocked by denial of service attack,which is the foremost web threat. This attack injects malicious traffics into the internet which deeplyaffects the availability of services. Categorizing the malicious traffic from normal traffic facilitatesthe elimination process. In view of eliminating the most victimized attacks which deny the servicesto the potential users, this paper proposes a classification method based on machine learning technique.The proposed SVM based classifier discriminates the HTTP attacks that intentionally blocksthe computing resources to the legitimate users based on network flow properties. The network flowproperties are selected by the proposed optimization method. The simulated results exhibit that withoptimized feature set, the classification performance of the proposed classifier using RBF kernel iscompetently higher when compared with other kernel models.
Nociceptin/Orphanin FQ Opioid Peptide-Receptor Expression in the Endometriosis-Associated Nerve Fibers—Possible Treatment Option?

Endometriosis (EM) is a chronic inflammatory disease affecting millions of women worldwide. Chronic pelvic pain is one of the main problems of this condition, leading to quality-of-life impairment. Currently, available treatment options are not able to treat these women accurately. A better understanding of the pain mechanisms would be beneficial to integrate additional therapeutic management strategies, especially specific analgesic options. To understand pain in more detail, nociceptin/orphanin FQ peptide (NOP) receptor expression was analyzed in EM-associated nerve fibers (NFs) for the first time. Laparoscopically excised peritoneal samples from 94 symptomatic women (73 with EM and 21 controls) were immunohistochemically stained for NOP, protein gene product 9.5 (PGP9.5), substance P (SP), calcitonin gene-related peptide (CGRP), tyrosine hydroxylase (TH), and vasoactive intestinal peptide (VIP). Peritoneal NFs of EM patients and healthy controls were positive for NOP and often colocalized with SP-, CGRP-, TH-, and VIP-positive nerve fibers, suggesting that NOP is expressed in sensory and autonomic nerve fibers. In addition, NOP expression was increased in EM associate NF. Our findings highlight the potential of NOP agonists, particularly in chronic EM-associated pain syndromes and deserve further study, as the efficacy of NOP-selective agonists in clinical trials.
ARIA Care Pathways 2019: Next-Generation Allergic Rhinitis Care and Allergen Immunotherapy in Malaysia

An increase in the prevalence of allergic rhinitis (AR) worldwide presents a significant burden to the health care system. An initiative was started in Europe designated as Allergic Rhinitis and Its Impact on Asthma (ARIA) to develop internationally applicable guidelines by utilising an evidence-based approach to address this crucial issue. The efforts are directed at empowerment of patients for self-management, the use of digital mobile technology to complement and personalise treatment, and establishment of real-life integrated care pathways (ICPs). This guideline includes aspects of patients’ and health care providers’ management and covers the main areas of treatment for AR. The model provides better real-life health care than the previous traditional models. This review summarises the ARIA next-generation guideline in the context of the Malaysian health care system.
Unexpected Characteristics of the Isoscalar Monopole Resonances in the A ~ 90 region - Implications for Nuclear Incompressibility

approximately 100% of the ISGMR (E0) energy-weighted sum rule was identified in each nucleus. In all cases the strength consisted of two components separated by 7-9 MeV. Except for the mass 92 nuclei, the upper component contained 14-22% of the E0 energy weighted sum rule (EWSR), however 38% and 65% of the E0 EWSR was located in the upper components in 92 Zr and 92 Mo respectively. The energies of the ISGMR for 92 Zr and 92 Mo are higher than for 90 Zr, suggesting a significant nuclear structure contribution to the energy of the ISGMR in these nuclei. This has a large effect on the compression modulus of the nucleus.
Salt enrichment and its deterioration in earthen sites in Emperor Qin’s Mausoleum Site Museum, China

Salt enrichment in the topsoil, owing to one-way migration of moisture from earthen sites to air environment, is an important inducement to weathering of sites and relics, such as efflorescence, recess, slice-peeling, which becomes the most important challenge to the preservation of unearthed sites and relics. Further, salt enrichments in the topsoil of undulating earthen sites are usually inhomogeneous such that it is difficult to precisely prevent the deterioration from happening of salt enrichment in the topsoil. A case study of salt enrichment at the K9901 funerary pit of Emperor Qin’s Mausoleum Site Museum was conducted by soil column experiment and numerical simulation. The water and salt transport in the earthen sites were simulated and analyzed by HYDRUS software. The simulation of the salt enrichment process at the earthen sites demonstrated that the enrichment of soluble salt ions mainly occurs on the surface of rammed earth and increases annually; the salt damage at the earthen sites can be effectively delayed by taking an environmental control measure. These results provide a reference for the prevention of salt damage at earthen sites and facilitate the daily management of earthen sites.
Expression of Chitinase and shRNA Gene Exhibits Resistance to Fungi and Virus

With the increasing global population, saving crops from diseases caused by different kinds of bacteria, fungi, viruses, and nematodes is essential. Potato is affected by various diseases, destroying many crops in the field and storage. In this study, we developed potato lines resistant to fungi and viruses, Potato Virus X (PVX) and Potato Virus Y (PVY), by inoculating chitinase for fungi and shRNA designed against the mRNA of the coat protein of PVX and PVY, respectively. The construct was developed using the pCAMBIA2301 vector and transformed into AGB-R (red skin) potato cultivar using Agrobacterium tumefaciens. The crude protein extract of the transgenic potato plant inhibited the growth of Fusarium oxysporum from ~13 to 63%. The detached leaf assay of the transgenic line (SP-21) showed decreased necrotic spots compared to the non-transgenic control when challenged with Fusarium oxysporum. The transgenic line, SP-21, showed maximum knockdown when challenged with PVX and PVY, i.e., 89 and 86%, while transgenic line SP-148 showed 68 and 70% knockdown in the PVX- and PVY-challenged conditions, respectively. It is concluded from this study that the developed transgenic potato cultivar AGB-R showed resistance against fungi and viruses (PVX and PVY).
Multiple-Sensor Detection System Design for Tea Identification Based on Mutual Information Array Optimization Scheme

In this article, a multimetal oxide sensor (MOS) detection system is developed for the identification of different grades of tea leaves. To cope with the interference brought by redundant information and further improve the detection capability of the system and reduce the number of sensors, sensor array optimization algorithms are further implemented. The main idea of sensor array optimization is to select sensors according to evaluation index which ranks the importance of sensors. This article optimizes the sensor array based on information theory. Specifically, a weighted modified mutual information (MI) optimization algorithm that simultaneously considers relevancy, redundancy, and complementarity is developed. The experimental results show that the weighted modified MI optimization method can obtain the best system performance with the minimum number of sensors.
Lifetime classic psychedelic use is associated with greater psychological distress in unemployed job seekers

Despite recent research linking lifetime classic psychedelic use to positive mental health outcomes, little work has explored the role played by classic psychedelics in healthy users' ability to cope with ordinary, yet stressful, life situations.This study begins to fill this gap by exploring whether lifetime classic psychedelic use is associated with attenuated or exacerbated psychological distress in unemployed job seekers.Drawing on openly-available data from the National Survey on Drug Use and Health (2013–2019) on 208,136 adults in the United States, this study tests whether lifetime classic psychedelic use interacts with employment status to predict differences in respondents' psychological distress experienced in the last 30 days.After adjusting for sociodemographics, health factors, and other substance use, unemployed job seekers with lifetime classic psychedelic use are found to report greater psychological distress relative to unemployed job seekers without lifetime psychedelic use. No differences in psychological distress based on lifetime classic psychedelic use were found in employed individuals.This study suggests that lifetime classic psychedelic use (of indoleamines specifically) may exacerbate stressful phases of life and provides context to previous studies linking lifetime classic psychedelic use to predominantly positive mental health outcomes in healthy populations.This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Furthermore, the author declares that there is no conflict of interest.
Teaching Grammar through Inductive Approach and Competence of Prospective Teachers

In Pakistan, traditional grammar teaching is not fruitful as students are notperforming better. It was needed to find new grammar teaching method.So, the study aimed to see the effect of inductive grammar teachingapproach on the teaching competence of prospective teachers. The studywas quasi experimental by design. The major hypothesis of the study wasthe difference of observed grammar teaching competence of theprospective teachers taught grammar through inductive teaching approachand traditional teaching is not significant.