Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteome-Wide Differential Effects of Peritoneal Dialysis Fluid Properties in an In Vitro Human Endothelial Cell Model

To replace kidney function, peritoneal dialysis (PD) utilizes hyperosmotic PD fluids with specific physico-chemical properties. Their composition induces progressive damage of the peritoneum, leading to vasculopathies, decline of membrane function, and PD technique failure. Clinically used PD fluids differ in their composition but still remain bioincompatible. We mapped the molecular pathomechanisms in human endothelial cells induced by the different characteristics of widely used PD fluids by proteomics. Of 7894 identified proteins, 3871 were regulated at least by 1 and 49 by all tested PD fluids. The latter subset was enriched for cell junction-associated proteins. The different PD fluids individually perturbed proteins commonly related to cell stress, survival, and immune function pathways. Modeling two major bioincompatibility factors of PD fluids, acidosis, and glucose degradation products (GDPs) revealed distinct effects on endothelial cell function and regulation of cellular stress responses. Proteins and pathways most strongly affected were members of the oxidative stress response. Addition of the antioxidant and cytoprotective additive, alanyl-glutamine (AlaGln), to PD fluids led to upregulation of thioredoxin reductase-1, an antioxidant protein, potentially explaining the cytoprotective effect of AlaGln. In conclusion, we mapped out the molecular response of endothelial cells to PD fluids, and provided new evidence for their specific pathomechanisms, crucial for improvement of PD therapies.
Optimal set-point regulation in HVAC system for controllability and energy efficiency

ABSTRACT The energy management of heating, ventilating, and air-conditioning (HVAC) system is a primary concern in building projects. Although they allow us to identify opportunities for effective energy use, their⁠ cost can sometimes exceed the energy saved. On the contrary, controller tuning by e.g. set-point regulation, often provides solutions that incur relatively low or no extra cost. In this paper, a simulation-based optimization approach is proposed for the optimal set-point regulation of HVAC system. For this purpose, we developed dynamic models for the target HVAC system that can simulate system behaviour at intervals of one minute. The set-point values were optimized while assessing controllability. The optimization of set-points that considered only energy efficiency led to various faults and therefore, was not applicable. However, optimal set-points obtained by considering controllability can help avoid significant faults.
Isotopic Equilibration in Convective Downdrafts

While it is becoming increasingly clear that stable water isotopologues are important tools in the study of atmospheric convection, many questions remain on how different processes affect them. This work is focused on water vapor isotopes in precipitation‐driven downdrafts. Using idealized simulations, the contributions of rain evaporation and liquid‐vapor equilibration processes are analyzed. It is shown that rain evaporation tends to deplete water vapor isotopes throughout the downdraft's descent, whereas equilibration has a neutral or depleting effect in the first half of the downdraft's life cycle and an enriching one in the second half. The total contribution of the two processes is then discussed, and it is argued that equilibration has an overall small effect compared to rain evaporation. Finally, using two sensitivity experiments, it is shown that the role played by equilibration varies significantly in regimes with different concentrations of cloud condensation nuclei.
Immunohistochemical Demonstration of the pGlu79 α-Synuclein Fragment in Alzheimer’s Disease and Its Tg2576 Mouse Model

The deposition of β-amyloid peptides and of α-synuclein proteins is a neuropathological hallmark in the brains of Alzheimer’s disease (AD) and Parkinson’s disease (PD) subjects, respectively. However, there is accumulative evidence that both proteins are not exclusive for their clinical entity but instead co-exist and interact with each other. Here, we investigated the presence of a newly identified, pyroglutamate79-modified α-synuclein variant (pGlu79-aSyn)—along with the enzyme matrix metalloproteinase-3 (MMP-3) and glutaminyl cyclase (QC) implicated in its formation—in AD and in the transgenic Tg2576 AD mouse model. In the human brain, pGlu79-aSyn was detected in cortical pyramidal neurons, with more distinct labeling in AD compared to control brain tissue. Using immunohistochemical double and triple labelings and confocal laser scanning microscopy, we demonstrate an association of pGlu79-aSyn, MMP-3 and QC with β-amyloid plaques. In addition, pGlu79-aSyn and QC were present in amyloid plaque-associated reactive astrocytes that were also immunoreactive for the chaperone heat shock protein 27 (HSP27). Our data are consistent for the transgenic mouse model and the human clinical condition. We conclude that pGlu79-aSyn can be generated extracellularly or within reactive astrocytes, accumulates in proximity to β-amyloid plaques and induces an astrocytic protein unfolding mechanism involving HSP27.
Diagnostic Utility of Cytokeratin 17 Expression in Oral Squamous Cell Carcinoma: A Review

One of the most common oral malignancies is oral squamous cell carcinoma (OSCC). Although the prevalence of oral cancer varies worldwide, it is generally agreed that the oral cavity is a common anatomical site for cancer, depending primarily on the country (and even particular region in some countries) and gender of the patients. Finding diagnostic markers for OSCC is critical for early diagnosis and personalised treatment of patients. Because they are overexpressed in OSCC relative to normal mucosa, cytokeratins (CKs), intermediate filaments of the cytoskeletons, are possibilities for diagnostic markers of OSCC. CK17 should be targeted as a diagnostic marker for OSCC among the CKs, as multiple other CKs have been linked to the disease. This study aims to assess the immuno-histochemistry expression of CK17 and to investigate whether there is a link between CK17 and OSCC differentiation.
Catching Up: An Observational Study of Underserved Primary and Secondary Student Mindsets When Introduced to Educational Robotics

Student attitudes toward STEM subjects decline as they progress through primary and secondary school, making interventions even more critical for students in these age groups. Integrating educational robotics into the classroom has been shown to increase student perceptions of STEM topics while also having many other positive learning benefits such as increased mastery of STEM concepts and STEM degree achievement. Furthermore, research on mindset in school-aged children found that students who held growth mindset beliefs had higher learning outcomes, persistence, and self-esteem compared to students who held fixed mindset beliefs. In this observational study, an educational robotics curriculum was implemented across grades 3–8 in an urban private school consisting primarily of underserved, minority students. The same robotics kit was used across all ages with differentiation in the STEM labs taught to different ages. The technology teacher—the principal investigator for this study—recorded results from a growth mindset survey and journaled about student reactions to the robotics curriculum as the school year progressed. Observations about student prior experience, attitudes, self-beliefs, and mastery are used to draw insights on the effects of educational robotics for underserved student populations. As the body of research on STEM learning through educational robotics expands and robotics increasingly becomes considered a standard in primary and secondary education, it is critical to consider the needs of students encountering robotics for the first time and how to support and grow their attitudes and mindsets. experience with robotics. Through observation and journaling, patterns emerged related to student mindset on ability. This study aims to provide initial findings on mindsets of traditionally underserved students through a brief survey as well as an analysis of the teacher’s observations. As studies have found that mindsets are meaningful for minority and low-income students (Aronson et al., 2002; Claro et al., 2016), investigating how the students at STBCA perceive their ability when introduced to educational robotics can provide insights into future practices to benefit students.
The Usability of IT Systems in Document Management, Using the Example of the ADPIECare Dorothea Documentation and Nurse Support System

Background: In 2016, an IT system was developed at MUL for the documentation of nursing practice. Preparing nursing students for the implementation of eHealth solutions under simulated conditions is crucially important for achieving the digital competencies necessary for health care systems in the future. Scientific evidence demonstrates that the use of an IT system in clinical practice shortens the time required for the preparation of documentation, increases the safety of clinical decisions and provides data for analysis and for the creation of predictive models for the purposes of HB HTA. Methods: The system was created through the cooperation of an interprofessional team at the Medical University of Łódź. The ADPIECare system was implemented in 2016 at three universities in Poland, and in 2017 a study of its usability was conducted using a questionnaire made available by Healthcare Information and Management Systems Society, “Defining and Testing EMR Usability MASTER V2 Final” on 78 nurses—students of MA in Nursing at Medical University of Łódź. Findings: Over 50% of the surveyed nurses indicated the usability of the system for the “effectiveness of documentation” variable. The same group of respondents had a positive attitude towards patient care planning with the use of the assessed system. In the opinions of the examined parties, positive opinions predominated, such as, e.g., “the system is intuitive”, “the system facilitates work”, “all patient assessments are in one place”, and “the time needed for data entry would be shortened”.
MR-TopoMap: Multi-Robot Exploration Based on Topological Map in Communication Restricted Environment

Multi-robot exploration in unknown environments is a fundamental task for a multi-robot system, involving inter-robot communication through messages among the robots. However, in a restricted communication environment, the limited communication resources become the system's bottleneck due to a large amount of data in the occupancy grid map. Hence, to enhance multi-agent exploration in communication-constrained environments, this letter develops a method to build topological maps while the robot moves in the environment and an exploration strategy based on the created topological map. The latter map comprises a set of vertices and edges connecting the vertices, where each vertex represents a specific area embedded with a descriptor extracted by visually observing this area and recognizing it utilizing descriptors. Each robot has its local grid map stored for path planning, not shared between them. Considering the exploration task, a robot's ability to choose a proper direction depends on the other robot's locations and the unexplored areas. Our exploration framework is evaluated on the Gazebo simulator and real robots, increasing the exploration efficiency by 23%$\sim$77%. Compared with the occupancy grid map scheme, our method's data transfer is reduced by 84%$\sim$90%.
Deepening the Whole Transcriptomics of Bovine Liver Cells Exposed to AFB1: A Spotlight on Toll-like Receptor 2

Aflatoxin B1 (AFB1) is a food contaminant metabolized mostly in the liver and leading to hepatic damage. Livestock species are differently susceptible to AFB1, but the underlying mechanisms of toxicity have not yet been fully investigated, especially in ruminants. Thus, the aim of the present study was to better characterize the molecular mechanism by which AFB1 exerts hepatotoxicity in cattle. The bovine fetal hepatocyte cell line (BFH12) was exposed for 48 h to three different AFB1 concentrations (0.9 µM, 1.8 µM and 3.6 µM). Whole-transcriptomic changes were measured by RNA-seq analysis, showing significant differences in the expression of genes mainly involved in inflammatory response, oxidative stress, drug metabolism, apoptosis and cancer. As a confirmatory step, post-translational investigations on genes of interest were implemented. Cell death associated with necrosis rather than apoptosis events was noted. As far as the toxicity mechanism is concerned, a molecular pathway linking inflammatory response and oxidative stress was postulated. Toll-Like Receptor 2 (TLR2) activation, consequent to AFB1 exposure, triggers an intracellular signaling cascade involving a kinase (p38β MAPK), which in turn allows the nuclear translocation of the activator protein-1 (AP-1) and NF-κB, finally leading to the release of pro-inflammatory cytokines. Furthermore, a p38β MAPK negative role in cytoprotective genes regulation was postulated. Overall, our investigations improved the actual knowledge on the molecular effects of this worldwide relevant natural toxin in cattle.
The modelling, design and the operation of an electromagnetic torque converter

The current hydraulic torque converter has many drawbacks. It requires a significant amount of oil to drive the impeller, and the turbine, which may cause a loss of energy. In addition, the direct contact of the mechanical parts of the conventional hydraulic torque converter increases the possibility of parts failure and mechanical noise. This thesis proposes a new and novel Electromagnetic Torque Converter (EMTC) system, which replaces the conventional hydraulic torque converter. The new EMTC system comprises of two parts, a Differential Machine (DM) part, which is a double rotor single stator machine, and a Variable Frequency Rotary Transformer (VFRT) part, which is responsible for transferring the slip power from between the DM rotors to the DM stator. One of the purposes the VFRT is to eliminate the use of slip rings. In addition, an electronic power converter is used in the EMTC system to convert the frequency of the slip power for re-injection into the DM. Finite Element Modelling (FEM) simulations were primarily used to define the design specifications of an experimental prototype EMTC system. These specifications include the minimum cogging torque, the ripple torque, and the high electromagnetic torque of the DM. FEM simulations were also used to select the stator slot configuration and for predicting the dynamic behaviour of each part of the EMTC system, and a mathematical model was developed. Each part of the EMTC system was characterised experimentally. The complete EMTC system was then tested in both open and closed loop configurations. The FEM simulations and the mathematical model showed good agreement with the experimental results. The new EMTC system resolves many of the drawbacks of the conventional hydraulic torque converter. The outcome of this thesis is expected to provide a step change in electromagnetic converter technology.
Salmonella enterica Serovar Typhimurium and Enteritidis Isolated from Raw Shrimp in Bangladesh: An Investigation Based on Molecular Characteristics, Survival, Virulence, Antibiotic Resistance, and Biofilm Formation Attributes

Shrimp is the white gold of Bangladesh, with the second-highest income source from exporting to foreign countries. Contamination with Salmonella spp. is now one of the significant issues for Bangladesh to export. Proper characterization of the salmonella pathogen is thus necessary to avoid undesirable losses due to the rejection of exported shrimp. In Bangladesh, the present condition of raw shrimp contamination with pathogenic Salmonella serovars and their survival/virulence properties was not adequately characterized. In this study, we collected 43 raw shrimps as samples from different farms in Jashore, Khulna, and Sathkhira regions. We then maintained standard cultural and biochemical protocols for isolating Salmonella strains, followed by the molecular identification of particular Salmonella serovars. The standard method for checking its credibility to form biofilm in 0–10% NaCl, tolerate acid/bile stress likewise in the gastrointestinal tract, and resist antimicrobial pressure was performed individually with the particular pathogenic strains. Our results successfully identified eleven Salmonella strains with three typhimurium serovars and three enteritidis serovars, which have biofilm-forming capability up to 4–8% NaCl, acid/bile habituation alike stomach/small intestine of humans, and resistance against necessary antibiotics generally used in treating human and poultry infection signifying the impending danger in the shrimp industry. While previous studies of Bangladesh successfully isolated Salmonella only presumptively, our research focused mainly on molecular characterization of the human Salmonella pathogen along with important survival and virulent attributes, such as biofilm formation, acid/bile tolerance, and antibiotic resistance of selected S. typhimurium and S. enteritidis strains. Further study with more sampling will be necessary to confer the transmission route of the pathogen from the natural reservoir to the shrimp industry.
A new prediction model of electricity load based on hybrid forecast engine

ABSTRACT In this paper, a new prediction model is introduced based on hybrid forecast engine and new feature selection. In this model, the load signal is filtered by feature selection to filter out the best candidates. Then, the proposed forecast engine is predicted the output of feature selection. In this model, the weights of proposed forecast engine are optimised by an intelligent algorithm to increase its accuracy. Effectiveness of the proposed method is applied over real-world engineering test case and compared with other different well-known methods. Obtained results proof the validity of the proposed method.
Efficient Recurrent Residual Networks Improved by Feature Transfer

Over the past several years, deep and wide neural networks have achieved great success in many tasks. However, in real life applications, because the gains usually come at a cost in terms of the system resources (e.g., memory, computation and power consumption), it is impractical to run top-performing but heavy networks such as VGGNet and GoogleNet directly on mobile and embedded devices, like smartphones and cameras. To tackle this problem, we propose the use of recurrent layers in residual networks to reduce the redundant information and save the parameters. Furthermore, with the help of feature map knowledge transfer, the performance of Recurrent Residual Networks (ReResNet) can be improved so as to reach similar accuracy to some complex state-of-the-art architectures on CIFAR-10, even with much fewer parameters. In this paper, we demonstrate the efficiency of ReResNet possibly improved by Feature Transfer on three datasets, CIFAR-10, Scenes and MiniPlaces.
Nitrogen Fertilizer and Nitrapyrin for Greenhouse Gas Reduction in Wolfberry Orchards on the Qinghai–Tibetan Plateau

Wolfberry production has become a major agro-industry on the Qinghai–Tibetan Plateau, causing increased nitrogen (N) pollution and greenhouse gas (GHG) emissions. Appropriate N fertilizer rate and nitrification inhibitors may mitigate GHG emissions and improve N use efficiency. A 2-year field experiment was conducted to measure the effects of N application rate and nitrapyrin on GHG emissions, to reduce GHG emissions and N pollution. We used eight treatments: Control (CK), 667 kg·ha−1 N (Con), 400 kg·ha−1 N (N400), 267 kg·ha−1 N (N267), 133 kg·ha−1 N (N133), 400 kg·ha−1 N plus 2.00 kg·ha−1 nitrapyrin (N400I2.00), 267 kg·ha−1 N plus 1.33 kg·ha−1 nitrapyrin (N267I1.33) and 133 kg·ha−1 N plus 0.67 kg·ha−1 nitrapyrin (N133I0.67). Compared with Con treatment, N400 maintained fruit yield and increased net income, but saved 40% of N fertilizer and decreased the cumulative N2O emission by 14–16%. Compared to N400, N267 and N133 treatments, the cumulative N2O emission of N400I2.00, N267I1.33 and N133I0.67 treatments was reduced by 28.5–45.1%, 26.6–29.9% and 33.8–45.9%, respectively. Furthermore, N400I2.00 resulted in the highest wolfberry yield and net income. The emissions of CH4 and CO2 were not significantly different among treatments. Moreover, the global warming potential (GWP) and the greenhouse gas emission intensity (GHGI) of N400I2.00 declined by 45.6% and 48.6% compared to Con treatment. Therefore, 400 kg·ha−1 N combined with 2.00 kg·ha−1 nitrapyrin was shown to be a promising management technique for maintaining wolfberry yield while minimizing GWP and GHGI.
Characteristics of Tight Oil Reservoir Based on Nano-CT

Besides biotechnology, nano-CT, the ideal technology, can also be used to observe three-dimensional nanostructures in intact cells as part of research into the characteristics of tight oil characteristics. There are few applications in the process and it is still in the early stage of development, but the advantages shown by 3D nanostructure technology are very strong and have strong applicability. Even in the face of tight oil reservoirs with poor physical properties, rapid decline in oil production after volume fracturing, and low oil recovery, it also shows very strong advantages. In order to promote the study of tight oil characteristics and avoid various problems, this article studies the characteristics of tight oil reservoirs based on nano-CT. The results show that the introduction of nano-CT technology into the study of tight oil reservoir characteristics can meet the market demand of tight oil and increase by 3.54%. It can continuously expand and develop rich oil resources under the condition of protecting geology and reservoirs, providing strong technical support for the next generation of large-scale tight oil storage and efficient growth, and can be used to a certain extent for research. The resulting reservoir characteristics solve the problem of excess resources.
Text to Song Synchronization Using Deep Neural Network

The most crucial aspect of the learning process is memory. There is no knowledge without memory. But most people lack memory because they memorize things through rote memorization. So in this paper, we have implemented a DNN model that converts plain text into a song which is done by synchronization of a midi file or the music with the text. MIDI files are symbolic representations of the music score. The melodic line of the composition is normally on one of them, while the background music is on the others. Analyzing the audio to identify voice portions in the audio where a human voice is present, as well as non-voice segments in proximity to the voice segments, is part of a method for syncing text with audio. The text segments of segmented text related to the audio can be recognized and synchronized to the speech segments.