Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Relationship Between the Expression Level of Mucin Gene Cluster (MUC2, MUC5A, and MUC5B) and Clinicopathological Characterization of Colorectal Cancer

Background: Colorectal cancer (CRC) is one of the most common cancers in the world and has a high mortality rate. It is accepted that dysfunction in the expression of mucins are associated with the occurrence and development of CRC. Therefore, the present study aimed to investigate the expression of MUC2, MUC5A, and MUC5B genes in CRC and their relationship with clinicopathological variables. Materials and Methods: The population included 28 patients after a colonoscopy and confirmation of the results. Tumors and parallel adjacent normal tissues from CRC patients were collected. RNA extraction and cDNA synthesis were performed using the corresponding kits. The gene primer was designed and RT-PCR was used to evaluate gene expression. The t-test and ANOVA were used to examine the differences between the different groups. Data analysis was performed using Prism8 software. Tumors from CRC patients were retrospectively collected from Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Results: The results showed that the expression of MUC2, MUC5A, and MUC5B genes was lower in patients with CRC aged 50 years or younger than was in older patients (P<0.05). Only the MUC5B gene expression was associated with tumor grades, which was higher in poorly differentiated tumors. The expression of MUC5A and MUC2 genes was higher in stage IV of the tumor than in other stages (P<0.05). Conclusion: Among the changes in the expression of MUC secretory genes, including MUC2, MUC5A, and MUC5B and clinicopathological variables, there was a relationship that could have prognostic and diagnostic value in CRC. Conclusion: None.
Real-Time SCADA Cyber Protection Using Compression Techniques

The Department of Energy’s Office of Electricity Delivery and Energy Reliability (DOE-OE) has a critical mission to secure the energy infrastructure from cyber attack. Through DOE-OE’s Cybersecurity for Energy Delivery Systems (CEDS) program, the Idaho National Laboratory (INL) has developed a method to detect malicious traffic on Supervisory, Control, and Data Acquisition (SCADA) network using a data compression technique. SCADA network traffic is often repetitive with only minor differences between packets. Research performed at the INL showed that SCADA network traffic has traits desirable for using compression analysis to identify abnormal network traffic. An open source implementation of a Lempel-Ziv-Welch (LZW) lossless data compression algorithm was used to compress and analyze surrogate SCADA traffic. Infected SCADA traffic was found to have statistically significant differences in compression when compared against normal SCADA traffic at the packet level. The initial analyses and results are clearly able to identify malicious network traffic from normal traffic at the packet level with a very high confidence level across multiple ports and traffic streams. Statistical differentiation between infected and normal traffic level was possible using a modified data compression technique at the 99% probability level for all data analyzed. However, the conditions tested were rather limited more » in scope and need to be expanded into more realistic simulations of hacking events using techniques and approaches that are better representative of a real-world attack on a SCADA system. Nonetheless, the use of compression techniques to identify malicious traffic on SCADA networks in real time appears to have significant merit for infrastructure protection. « less
Malay Version of Moral Identity Scale: A Cross-Cultural Validation In Malaysian Youth

Introduction: The Moral Identity Scale (MIS) measures the construct of moral identity – internalization and symbolization. This study aims to translate and validate the original English version of MIS to the Malay language version. Methods: The 10 items of MIS (five items of symbolization and five items of internalization) were translated to the Malay language through forward and backward procedures. A total of 388 youth-aged participants were involved in this online survey. Participants’ age ranged from 18-24 years old. More than half were females. Results: The construct of moral identity was maintained with the re-modeling of internalization. The final model suggested retaining the three internalization items and five symbolization items. Discriminant validity and the construct reliability of the two factors were satisfactory (symbolization=0.81, internalization=0.69). Internal consistencies indicated acceptable Cronbach’s alpha values for both symbolization (0.85) and internalization (0.81). Test-retest Intraclass Correlation Coefficient (ICC) was good and satisfactory (internalization=0.79 and symbolization=0.81). Conclusion: The Malay version of MIS is a reliable tool and free from cultural bias which is useful to be applied in a public health-related program.
Regionalized nitrogen fate in freshwater systems on a global scale

Excessive nitrogen (N) use in agriculture, industry, and household waste leads to widespread N release throughout the environment, causing eutrophication in both freshwater and coastal areas. To better understand N‐induced eutrophication and other N‐use‐related environmental impacts at the local scale, improvements in the spatial resolution of life cycle impact assessment measures are required. Here, we present a method to estimate gridded fate factors (FFs) at a half‐degree resolution based on the Integrated Model to Assess the Global Environment‐Global Nutrient Model to provide eutrophication indicators for global N‐related manufacture, trade, and consumption in life cycle assessment. Across global freshwater systems, our cumulative FFs have a 5th percentile of 0.9 days and a 95th percentile of 184.0 days. Aggregated FFs for administrative units range from 0.3 days to 211.9 days. The hotspots of cumulative FFs are mainly distributed upstream of large reservoirs or lakes. On a global level, advection is the dominant process controlling the FF (69.7% of areas), followed by retention (29.0%), and water consumption (1.3%). N retention dominates in advection‐favoring, high‐discharge regions due to the high residence times, while water consumption tends to dominate water‐scarce zones. The results demonstrate the importance of gridded information to assess eutrophication impacts, as it characterizes N emissions from anthropogenic sources at high spatial resolution in comparison to basin‐ or country‐level assessments. Introducing soil–freshwater N fate complements existing P‐related fates to improve global assessments of eutrophication. This article met the requirements for a Gold–Gold Badge JIE data openness badge described at http://jie.click/badges
Blood filters in children with COVID‐19 and acute kidney injury: A review

COVID‐19 has challenged the global healthcare system through rapid proliferation and lack of existing treatment resulting in over 180 million cases and 3.8 million deaths since December 2019. Although pediatric patients only comprise 1%–2% of diagnosed cases, their incidence of acute kidney injury ranges from 8.2% to 18.2% compared to 49% in adults. Severe infection, initiated by dysregulated host response, can lead to multiorgan failure. In this review, we focus on the use of various blood filters approved for use in pediatric kidney replacement therapy to mitigate adverse effects of severe illness. Therapeutic effects of these blood filters range from cytokine removal (CytoSorb, HA330, HCO/MCO), endotoxin removal (Toraymyxin, CPFA), both cytokine and endotoxin removal (oXiris), and nonspecific removal of proteins (PMMA) that have already been established and can be used to mitigate the various effects of the cytokine storm syndrome in COVID‐19.
State observer-based sliding mode control for semi-active hydro-pneumatic suspension

Abstract This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.
Estimation of graphical models for skew continuous data

We consider a new approach for estimating non‐Gaussian undirected graphical models. Specifically, we model continuous data from a class of multivariate skewed distributions, whose conditional dependence structure depends on both a precision matrix and a shape vector. To estimate the graph, we propose a novel estimation method based on nodewise regression: we first fit a linear model, and then fit a one component projection pursuit regression model to the residuals obtained from the linear model, and finally threshold appropriate quantities. Theoretically, we establish error bounds for each nodewise regression and prove the consistency of the estimated graph when the number of variables diverges with the sample size. Simulation results demonstrate the strong finite sample performance of our new method over existing methods for estimating Gaussian and non‐Gaussian graphical models. Finally, we demonstrate an application of the proposed method on observations of physicochemical properties of wine.
Low-Voltage Ride Through Enhancement of Both DFIG and SEIG-Based Wind Power Plants by RC-Type Solid-State Fault Current Limiter

Abstract The low-voltage ride-through (LVRT) is the main requirement of grid codes for integration of wind power plants (WPPs) to the power system. This paper proposes a RC-type solid state fault current limiter (SSFCL) to enhance the LVRT requirement of WPPs. It is based on the RL-type SSFCL in which its configuration is changed to satisfy the LVRT requirements. To evaluate the proposed RC-type SSFCL performance, extended time domain simulations are executed in PSCAD/EMTDC software environment. Also, the performance of the RC-type and RL-type SSFCLs are compared under both symmetrical and asymmetrical fault conditions to show the efficiency of the proposed RC-type SSFCL. Both doubly-fed induction generator (DFIG) and self-excited induction generator (SEIG) are used to examine the RC-type SSFCL performance. Based on simulation results, the RC-type SSFCL provides an effective hardware scheme to augment the LVRT requirements of both DFIG and SEIG based WPPs and outperforms the RL-type SSFCL.
Nanotechnologies in medical devices

Nanotechnologie wordt steeds meer gebruikt voor medische hulpmiddelen. Talrijke medische disciplines profiteren van de innovaties die nanotechnologie mogelijk maakt. Ook neemt de kennis over hoe je de veiligheid van nanotechnologie moet beoordelen toe. Recente wetenschappelijke leidraden geven aan waarop moet worden gelet als nanotechnologie wordt gebruikt bij de fabricage van een medisch hulpmiddel. Kennis en leidraden vormen daarmee een goede basis om de risicobeoordeling van nanomedische hulpmiddelen uit te voeren. Dit blijkt uit een overzicht van het RIVM van het gebruik van nanotechnologie voor medische hulpmiddelen. Een van de belangrijkste trends is het gebruik van nanocoatings op allerlei implantaten. Hierdoor integreert het implantaat beter met het omliggende weefsel, wat de kans op afstoten of complicaties verkleint. Onder andere de cardiologie (coating op stents), orthopedie (coatings op heupimplantaat) en tandheelkunde (tandheelkundige implantaten) profiteren hiervan. Verder worden antimicrobiele eigenschappen van nanomaterialen gebruikt in coatings, voor wondverzorging en medisch textiel. Nanomaterialen kunnen ook natuurlijke weefsels nabootsen. Met behulp van nanotechnologie kunnen bij implantaten optimale biologische, fysische en mechanische eigenschappen worden gerealiseerd. Een derde trend hangt samen met de elektrische en magnetische eigenschappen van nanomaterialen. Deze worden vooral gebruikt in medische hulpmiddelen voor neurologie en cardiologie, bijvoorbeeld om hartritmestoornissen beter te verhelpen. Ook kunnen batterijen met een langere levensduur worden ontwikkeld voor implantaten. Een specifieke toepassing van nanotechnologie is oncologie. Voorbeelden zijn testen om kanker vroegtijdig op te sporen en hulpmiddelen om de grenzen te bepalen van tumoren of uitzaaiingen te detecteren tijdens een chirurgische ingreep. Ook kunnen nanomaterialen door lokale temperatuurverhogingen het effect van chemotherapie of bestraling versterken, of zelfs direct tumorcellen doden. Net als bij alle medische producten moet de risicobeoordeling van nanomedische hulpmiddelen per product worden uitgevoerd. De kans dat een nanomateriaal vrij beschikbaar komt in het lichaam, bepaalt hoe diepgaand de 'nano' risicobeoordeling moet zijn.
Rail track condition monitoring: a review on deep learning approaches

Rail track is a critical component of rail systems. Accidents or interruptions caused by rail track anomalies usually possess severe outcomes. Therefore, rail track condition monitoring is an important task. Over the past decade, deep learning techniques have been rapidly developed and deployed. In the paper, we review the existing literature on applying deep learning to rail track condition monitoring. Potential challenges and opportunities are discussed for the research community to decide on possible directions. Two application cases are presented to illustrate the implementation of deep learning to rail track condition monitoring in practice before we conclude the paper.
Fabrication of Metallic Microneedle by Electroplating and Sharpening of it by Electrochemical Etching

Aiming at the use in low-invasive medical treatments, this paper reports a fabrication of metallic microneedle, which has a three-dimensionally sharp tip. Compared to a silicon or polymer needle which we previously proposed, a metallic needle has toughness to evade breakage. Even if it is broken, it does not become small pieces thanks to its ductility, which increases the safety for a human body. A nickel needle was fabricated using electroplating, followed by sharpening it by electrochemical etching. A smooth tip surface is obtained due to electrochemical etching reactions. Sharpness and smoothness of the tip are effective for easy insertion in the viewpoint of large stress concentration and small friction, respectively. An experiment of inserting the fabricated needle into an artificial skin of silicone rubber was carried out. The resistance force during insertion was much reduced compared to that of commercial stainless needle (23 G: shank diameter 650 µm). Although a fabricated metallic needle was inserted and pulled-out for several times, it was not broken in any trial. By changing the angle between object surface and needle axis, the insertion experiments were carried out. Fabricated nickel needle was not broken for any angle, while silicon needle was broken in case the angle is small, i.e., the needle is much inclined from normal direction of the surface, which ensures the safety of metallic microneedle to human body in the viewpoint of breakage.
Cropping Up Crisis at the Nexus Between COVID-19 and Antimicrobial Resistance (AMR) in Africa: A Scoping Review and Synthesis of Early Evidence

In this study, we aim to synthesize some evidence on the impacts that coronavirus disease 2019 (COVID-19) is having on the epidemiology of antimicrobial resistance (AMR) in Africa since it was declared a global pandemic by the WHO in March 2020. A scoping review was undertaken by collecting and curating relevant resources from peer-reviewed articles and also from the gray literature. Mixed approaches of extracting data (qualitative and quantitative) were employed in synthesizing evidence, as suggested by the Health Evidence Network. A model constructed based on the synthesis of early evidence available on the effects of factors linked to COVID-19 in impacting the evolution of AMR in Africa predicted that, in cumulative terms, those factors favoring the evolution of AMR outpace those disfavoring it by no less than three folds. COVID-19 is likely fueling the evolution of AMR almost unhindered in Africa. Due to the recognition of this crisis, concerted efforts for resource mobilization and global cooperation are needed to tackle it.
Call for Papers

The ability to engage in new thinking and new paradigms is a critical aspect of any discipline. Thankfully, the discipline of ergonomics has a long history of innovations in theory, methodology, science and application. For example, accident causation models that first emerged in the early 1900s have since evolved to consider entire systems and emergent properties (e.g. Heinrich 1931; Leveson 2004; Perrow 1984; Rasmussen 1997; Reason 1990). Similarly, methodologies have moved from focussing on tasks (Taylor 1911) to entire systems and the constraints shaping behaviour (e.g. Vicente 1999). The aim of this special issue is to provide researchers and practitioners with an opportunity to present and discuss contemporary, forecasted, and required paradigm shifts in ergonomics. We welcome submissions from all aspects of the discipline including physical, physiological, psychophysiological, psychological, cognitive, social, and organisational ergonomics. Manuscripts are welcomed on, but not restricted to:
USER INTENT PREDICTION FROM ACCESS LOG IN ONLINE SHOP

A lot of recommendation systems on online shops use user's order histories in order to determine recommendation items. In general recommendation systems items are selected based on neighbor users defined according to similarity among users using the order histories. However, the method cannot be applied to new users who have never purchased anything in an online shop and do not define the neighbor users based on their order histories because of undefined similarity. The problem is called a cold start problem. In order to overcome the problem we proposed a method which uses user's access logs to make user profile instead of his/her order histories. Although the access log is less reflective of the user’s preference than the order history, we can estimate their intent by careful access log analysis because the access log consists of user’s review processes for their purchase. Therefore, to clarify users' intent we use only web pages related to decision of order products strongly. And in order to find these web pages we analyze access logs of users who ordered the same product or the same category. Then we use these pages for making a user profile. In experiments we estimate neighbor users of new users using their user profiles constructed with access logs. And we predict a category of a product which the new users will purchase to examine the efficiency of our proposed method. From experiments we found that there were some categories in which the proposed method can correctly predict new user’s target, we confirmed the effectiveness of our proposed method as a solution for cold start problem. However, we found that we improved the proposed method to predict a product itself.
Realistic Assessment of Novel Wireless Systems with Ray-tracing Based Techniques

Ray tracing based on geometric optics can be utilized for generating propagation models for arbitrary and complex environments. These methods can be employed to determine important wireless channel characteristics such as path gain and the channel impulse response which in turn can be used to deduce channel capacity. In this thesis, a fully vectorial 3-D ray-tracer is developed. The simulator is applied to study novel wireless systems such as ultra-wideband pulse propagation in complex railway tunnels and MIMO systems employing closely spaced low mutual coupling meta-material antennas. The computational complexity of the ray-tracing algorithm is reduced using optimizations and via the development of a novel hybrid method that combines the efficiency and accuracy of waveguide models with the flexibility of a ray-tracer. The resulting simulator is validated against measured results and demonstrated to show good agreement. Convergence of the solution using the ray-tracing method is also discussed.
The opinions of prospective teachers on the design and use of digital educational comics as a technological teaching material in science education

In this study, it is aimed to examine the opinions of prospective teachers about the design of digital educational comics designed within the scope of science education and their use in educational environments. This study, conducted with 129 prospective teachers determined by purposeful sampling method, is suitable for a case study. After the prospective teachers received a four-hour training on digital educational comics, they designed their digital educational comics for two weeks. After the design process, their views on design and applicability of these designs were determined with structured survey forms. The collected data were analyzed in four stages with the MAXQDA-20 program in accordance with content analysis. In the study, it was determined that the prospective teachers had difficulties at the point of designing visual and graphical elements in digital environment during the digital educational comic design process and that they were negatively affected by technological insufficiencies. In addition to this, the prospective teachers expressed the views on the need to pay attention to the digital educational comic’s subject-acquisition relationship, scientific knowledge and the relationship of this knowledge with daily life. It is recommended to increase the use of technology-oriented alternative teaching materials such as digital educational comics in science education from preschool to undergraduate level instead of traditional teaching materials.
Are You Sure You Want to Use MMAP in Your Database Management System?

Memory-mapped ( mmap ) file I/O is an OS-provided feature that maps the contents of a file on secondary storage into a program’s address space. The program then accesses pages via pointers as if the file resided entirely in memory. The OS transparently loads pages only when the program references them and automatically evicts pages if memory fills up. mmap ’s perceived ease of use has seduced database management system (DBMS) developers for decades as a viable alternative to implementing a buffer pool. There are, however, severe correctness and performance issues with mmap that are not immediately apparent. Such problems make it difficult, if not impossible, to use mmap correctly and efficiently in a modern DBMS. In fact, several popular DBMSs initially used mmap to support larger-than-memory databases but soon encountered these hidden perils, forcing them to switch to managing file I/O themselves after significant engineering costs. In this way, mmap and DBMSs are like coffee and spicy food: an unfortunate combination that becomes obvious after the fact. Since developers keep trying to use mmap in new DBMSs, we wrote this paper to provide a warning to others that mmap is not a suitable replacement for a traditional buffer pool. We discuss the main shortcomings of mmap in detail, and our experimental analysis demonstrates clear performance limitations. Based on these findings, we conclude with a prescription for when DBMS developers might consider using mmap for file I/O.