Miracle-dz/UniFAR-FTUs huggingface dataset:
Disclosing Potential Key Genes, Therapeutic Targets and Agents for Non-Small Cell Lung Cancer: Evidence from Integrative Bioinformatics Analysis

Non-small-cell lung cancer (NSCLC) is considered as one of the malignant cancers that causes premature death. The present study aimed to identify a few potential novel genes highlighting their functions, pathways, and regulators for diagnosis, prognosis, and therapies of NSCLC by using the integrated bioinformatics approaches. At first, we picked out 1943 DEGs between NSCLC and control samples by using the statistical LIMMA approach. Then we selected 11 DEGs (CDK1, EGFR, FYN, UBC, MYC, CCNB1, FOS, RHOB, CDC6, CDC20, and CHEK1) as the hub-DEGs (potential key genes) by the protein–protein interaction network analysis of DEGs. The DEGs and hub-DEGs regulatory network analysis commonly revealed four transcription factors (FOXC1, GATA2, YY1, and NFIC) and five miRNAs (miR-335-5p, miR-26b-5p, miR-92a-3p, miR-155-5p, and miR-16-5p) as the key transcriptional and post-transcriptional regulators of DEGs as well as hub-DEGs. We also disclosed the pathogenetic processes of NSCLC by investigating the biological processes, molecular function, cellular components, and KEGG pathways of DEGs. The multivariate survival probability curves based on the expression of hub-DEGs in the SurvExpress web-tool and database showed the significant differences between the low- and high-risk groups, which indicates strong prognostic power of hub-DEGs. Then, we explored top-ranked 5-hub-DEGs-guided repurposable drugs based on the Connectivity Map (CMap) database. Out of the selected drugs, we validated six FDA-approved launched drugs (Dinaciclib, Afatinib, Icotinib, Bosutinib, Dasatinib, and TWS-119) by molecular docking interaction analysis with the respective target proteins for the treatment against NSCLC. The detected therapeutic targets and repurposable drugs require further attention by experimental studies to establish them as potential biomarkers for precision medicine in NSCLC treatment.
Application of Neural Networks in Video Game Simulation

: The subject of this paper is the development of 2D/3D video games using neural networks. The simulation method was used to design and program the video game Super Mario, which with its well-known functionality enables the application of artificial intelligence methods and neural networks. This paper aims to understand the relationship between the use of video games and their neural correlates, taking into account the whole range of cognitive factors that they include. The results of the research indicate the importance of using artificial neural networks in video games, bearing in mind that prediction is closely related to learning and that the existence of feedback allows game participants to evaluate their performance and increase the quality of future prediction of situations and moves. Despite the heterogeneity of the field of study, the research results indicate that it is possible to establish links between neural and cognitive aspects, especially in terms of attention, cognitive control, visual-spatial skills, cognitive load. However, many aspects could be improved. The lack of standardization in various aspects of video game-related research, such as participant characteristics, characteristics of each video game genre, and different goals, could contribute to disagreements with some related research.
Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices

With the advent of the Internet of Things (IoT), human-assistive technologies in healthcare services have reached the peak of their application in terms of diagnosis and treatment process. These devices must be aware of human movements to provide better aid in clinical applications as well as the user's daily activities. In this context, real-time gait analysis remains to be key catalyst for developing intelligent assistive devices. In addition to machine and deep learning algorithms, gait recognition systems have significantly improved in terms of high accuracy recognition. However, most of the existing models are focused on improving gait recognition while ignoring the computational overhead that affects the accuracy of detection and even remains unsuitable for real-time implementation. In this research paper, we proposed a hybrid gated recurrent unit (GRU) based on BAT-inspired extreme convolutional networks (BAT-ECN) for the effective recognition of human activities using gait data. The gait data are collected by implanting the wearable Internet of Things (WIoT) devices invasively. Then, a novel GRU and ECN networks are employed to extract the spatio-temporal features which are then used for classification to realize gait recognition. Extensive and comprehensive experimentations have been carried out to evaluate the proposed model using real-time datasets and also other benchmarks such as whuGait and OU-ISIR datasets. To prove the excellence of the proposed learning model, we have compared the model's performance with the other existing hybrid models. Results demonstrate that the proposed model has outperformed the other learning models in terms of high gait classification and less computational overhead.
Design, modeling and experiment of a miniature biped piezoelectric robot

A novel miniature biped piezoelectric robot (MBPR) was designed with a patch-type beam structure. The robot utilizes an asymmetric friction-inertial driving principle to realize linear motion. The prominent feature is that it can move linearly under low frequency and low voltage, which is beneficial for untethered driving of the robot. In addition, the robot has the advantages of simple structure, convenience for multi-degree-of-freedom extension and strong load capacity. The effect of different dimensional parameters on the motion of the MBPR was studied and a prototype was fabricated, whose size was 39 × 15 × 4 mm3 and weighed 0.9 g. The MBPR achieved a maximum speed of 0.4 body length per second. To expand the motion degree of freedom, an array of MBPR was fabricated and tested. The results indicated that the robot array realized linear motion of 1.3 mm s−1 and rotation motion of 1.6° s−1. The array could carry a load of 25 g (13.8 times self-weight), which shows strong load capacity based on its lightweight structure. Finally, we designed a robot consisted of the array and an untethered power supply, 2-DOF untethered motion could be realized on the plane, which was conducive to finish large-scale movement and tasks in narrow environments.
Transcriptome Sequencing to Identify Important Genes and lncRNAs Regulating Abdominal Fat Deposition in Ducks

Simple Summary Abdominal fat deposition affects the quality of duck meat and the feed conversion ratio. Here, we performed transcriptome sequencing of the abdominal adipose tissue of ducks with high and low abdominal fat rate by RNA sequencing, exploring the key regulatory genes and lncRNAs related to abdominal fat deposition. As a result, several candidate genes, lncRNAs, and pathways related to abdominal fat deposition in ducks were retrieved. This study lays the foundations for exploring molecular mechanisms underlying the regulation of abdominal fat deposition in ducks, providing a theoretical reference for breeding high-quality meat-producing ducks. Abstract Abdominal fat deposition is an important trait in meat-producing ducks. F2 generations of 304 Cherry Valley and Runzhou Crested White ducks were studied to identify genes and lncRNAs affecting abdominal fat deposition. RNA sequencing was used to study abdominal fat tissue of four ducks each with high or low abdominal fat rates. In all, 336 upregulated and 297 downregulated mRNAs, and 95 upregulated and 119 downregulated lncRNAs were identified. Target gene prediction of differentially expressed lncRNAs identified 602 genes that were further subjected to Gene Ontology and KEGG pathway analysis. The target genes were enriched in pathways associated with fat synthesis and metabolism and participated in biological processes, including Linoleic acid metabolism, lipid storage, and fat cell differentiation, indicating that these lncRNAs play an important role in abdominal fat deposition. PPAPA, FOXO3, FASN, PNPLA2, FKBP5, TCF7L2, BMP2, FGF2, LIFR, ZBTB16, SIRT, GYG2, NCOR1, and NR3C1 were involved in the regulation of abdominal fat deposition. PNPLA2, TCF7L2, FGF2, LIFR, BMP2, FKBP5, GYG2, and ZBTB16 were regulated by the lncRNAs TCONS_00038080, TCONS_0033547, TCONS_00066773, XR_001190174. 3, XR_003492471. 1, XR_003493494. 1, XR_001192142. 3, XR_002405656. 2, XR_002401822. 2, XR_003497063. 1, and so on. This study lays foundations for exploring molecular mechanisms underlying the regulation of abdominal fat deposition in ducks and provides a theoretical basis for breeding high-quality meat-producing ducks.
Evaluation of Energy Potential from Coffee Pulp in a Hydrothermal Power Market through System Dynamics: The Case of Colombia

Colombia has abundant solar, wind, and biomass resources for energy production with non-conventional renewable energy (NCREs) sources. However, the current participation of NCREs is negligible in the electricity mix of the country, which has historically depended on hydroelectric plants. Meteorological phenomena, such as the El Niño–Southern Oscillation (ENSO), threaten the energy supply during periods of drought, and the generation of energy using fossil fuels is necessary to offset the hydric deficit. Since Colombia is one of the largest coffee producers in the world, this study used system dynamics to evaluate the energy potential from cherry coffee pulp and analyze trends in the energy supply for different energy sources in scenarios of climatic vulnerability. First, the causal relationship of the system was identified, and the key variables of the model were projected. Then, the behavior of the system was evaluated by simulating a 120-month period. The results showed a generation potential from coffee pulp of 177 GWh per year and a power generation of 11,250 GWh and 7537 GWh with solar and wind resources, respectively, by 2030. Finally, it was confirmed that including new renewable resources is a key factor in supporting hydraulic generation in the warm phase of ENSO while reducing thermal generation dependence.
Analytical Solution for Bichromatic Waves on Linearly Varying Currents

It is well-known that the bound long waves play an important role on beach morphology. The existence of the current will modify the intensity of the waves. To examine the more realistic problem where the current is non-uniform, a third-order analytical solution for bichromatic waves on currents with constant vorticity is derived using a perturbation method. Earlier derivations of theories for interactions between waves and currents have been limited to cases of bichromatic waves on depth-uniform currents and cases of monochromatic waves on linear shear currents. Unlike the derivations of monochromatic waves, the moving-frame method cannot be used in the case of bichromatic waves because there are multiple waves with different celerities, and the flow can in no way be treated as steady-state. Moreover, for shear currents where the flows are rotational, the velocity potential cannot be simply defined. For these reasons, it is difficult to carry out mathematical operations when the dynamic free surface boundary condition is applied. However, with the consideration of the wave part of the fluid motion remaining irrotational, some of the terms in the expanded boundary conditions can be ignored; thus, the derivations can be further processed. As a result, the third-order explicit expressions for the stream function, the velocity potential, and the surface elevation can be solved. The nonlinear dispersion relation is also derived to account for interacting wave components with different frequencies and amplitudes which can be used to solved for wavenumbers of both wave trains. The obtained solutions are verified by reducing to those of previous results for monochromatic waves and uniform currents. Furthermore, the influence of constant vorticity on the wave kinematics is illustrated. A comparison between following/opposing currents is also carried out. Finally, the effects of the shear current on the strength of the bound long waves are also illustrated.
Integrated Carbon Footprint and Economic Performance of Five Types of Dominant Cropping Systems in China’s Semiarid Zone

Crop production requires large areas of land and makes an important contribution to greenhouse gas emissions. Cleaner production of all crop types could be of great significance to realizing carbon neutrality as soon as possible. The present study adopted life cycle assessment (LCA) combined with the profit accounting method of input-output to compare the differences in greenhouse gas emissions in the entire life cycle of apple (Malus pumila Mill.), grain maize (Zea mays L.), wheat (Triticum aestivum L.), silage maize (Zea mays L.), and alfalfa (Medicago sativa Linn.) production in eastern Gansu Province with three functional units, including per ha of land, per ton of product, and per 10,000 yuan of output value. The results showed that apple had the largest carbon footprint per ha. Wheat had the largest carbon footprint per ton of product and per 10,000 yuan output. The results of LCA inventory sensitivity analysis showed that the main sources of greenhouse gas emissions for all crops were the production process of agricultural materials such as chemical fertilizer, machinery, and agricultural film. In particular, the excessive input of chemical fertilizer was the driving factor resulting in greenhouse gas emissions. Based on the study results, this paper also puts forward certain suggestions on the future land use of the cropping systems in the study area.
Security analysis of Aspiro Music Platform, a digital music streaming service

The report is mainly based on recommendations given by the National Institute of Standards and Technology in special publication 800-30 “Risk Management Guide for Information Technology Systems”. The risk analysis presented in this report emphasizes a qualitative approach. Firstly, the security requirements for Aspiro Music Platform were identified and classified by the level of importance. Secondly, potential threats to the system were discussed. In the next step the potential system vulnerabilities were identified and presented in form of an attack tree. Afterwards, a penetration testing of the potentially vulnerable parts of the Aspiro Music Platform were performed. This step resulted in discovery of a few major and minor flaws as well as in creation of WiMP Number Dump. The latter is an experimental hacker tool that exploited weaknesses of getwimp.com webpage to create a list of WiMP subscribers, their telephone numbers and addresses. The results were used to asses the level of risk to Aspiro Music Platform by multiplying the ratings assigned for threat likelihood and threat impact. Lastly, some mitigation methods for identified risks were suggested.
A hybrid solution approach for the 3L-VRP with simultaneous delivery and pickups

This paper deals with a special vehicle routing problem with backhauls where each customer receives items from a depot and, at the same time, returns items back to the depot. Moreover, time windows are assumed and three-dimensional loading constraints are to be observed, i.e. the items are three-dimensional boxes and packing constraints, e.g. regarding load stability, are to be met. The resulting problem is the vehicle routing problem with simultaneous delivery and pickup (VRPSDP), time windows, and three-dimensional loading constraints (3L-VRPSDPTW). This problem occurs, for example, if retail stores are supplied by a central warehouse and wish to return packaging material. A particular challenge of the problem is to transport delivery and pickup items simultaneously on the same vehicle. In order to avoid any reloading effort during a tour, we consider two different loading approaches of vehicles: (i) loading from the back side with separation of the loading space into a delivery section and a pickup section and (ii) loading at the long side. A hybrid algorithm is proposed for the 3L-VRPSDPTW consisting of an adaptive large neighbourhood search for the routing and different packing heuristics for the loading part of the problem. Extensive numerical experiments are conducted with VRPSDP instances from the literature and newly generated instances for the 3LVRPSDPTW.
Lympho-Hematopoietic Microenvironments and Fish Immune System

Simple Summary Teleost fish, the most abundant group of vertebrates, represent an excellent tool to establish possible correlations between the histological organization of their lymphoid organs and their immunological capacities. This approach allows us to analyze embryonic and larval lymphopoiesis, the remarkable organization of the teleost thymus, the role of the kidney as a true equivalent of the lympho-hematopoietic bone marrow of higher vertebrates, the mechanisms of antigen trapping in both ellipsoids and the so-called melano-macrophage centers (MMCs) and their relation with the generation of memory and the lack of germinal centers, and the extended development of the lymphoid tissue associated to mucosae. Abstract In the last 50 years information on the fish immune system has increased importantly, particularly that on species of marked commercial interest (i.e., salmonids, cods, catfish, sea breams), that occupy a key position in the vertebrate phylogenetical tree (i.e., Agnatha, Chondrichtyes, lungfish) or represent consolidated experimental models, such as zebrafish or medaka. However, most obtained information was based on genetic sequence analysis with little or no information on the cellular basis of the immune responses. Although jawed fish contain a thymus and lympho-hematopoietic organs equivalents to mammalian bone marrow, few studies have accounted for the presumptive relationships between the organization of these cell microenvironments and the known immune capabilities of the fish immune system. In the current review, we analyze this topic providing information on: (1) The origins of T and B lymphopoiesis in Agnatha and jawed fish; (2) the remarkable organization of the thymus of teleost fish; (3) the occurrence of numerous, apparently unrelated organs housing lympho-hematopoietic progenitors and, presumably, B lymphopoiesis; (4) the existence of fish immunological memory in the absence of germinal centers.
Optimizing ride matches for dynamic ride-sharing systems

Ride-share systems, which aim to bring together travelers with similar itineraries and time schedules, may provide significant societal and environmental benefits by reducing the number of cars used for personal travel and improving the utilization of available seat capacity. Effective and efficient optimization technology that matches drivers and riders in real-time is one of the necessary components for a successful ride-share system. The research conducted in this dissertation formally defines dynamic or real-time ride-sharing, identifies optimization problems for finding best sets of ride-share matches in a number of operational scenarios, develops approaches for solving ride-share optimization problems, and tests the concepts via a simulation study of work trips in the Atlanta metropolitan area. The first chapter introduces the motivation of the ride-sharing problem and briefly defines the dynamic ride-sharing system. In Chapter 2, we systematically outline the optimization challenges that arise when developing technology to support ride-sharing and survey the related operations research models in academic literature. In Chapter 3, we develop optimization-based approaches for finding ride-share matches in a standard problem setting, with the goal of minimizing the total system-wide vehicle miles incurred by system users. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules substantially improves the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers. In Chapter 4, we consider a more sophisticated ride-share setting where participants may be unlikely to accept ride-share matches if they are not stable. Generically, a set of matches between riders and drivers is defined as stable if no rider and driver, currently matched to others, would prefer to be matched together. This notion of stability is similar to that of the stable marriage problem. We develop notions of stable ride-share matching in a variety of settings, and develop approaches for finding stable (or nearly-stable) solutions. Computational results are used to compare system performance under various levels of matching stability. A system with unstable matching assignments is simulated over two months in which participants are likely to reject the system's assignment if a private arrangement between individuals could bring better benefits. The simulation results indicate that the total savings generated by a ride-sharing system deteriorate with unstable matching assignments and that enforcing stability constraints in matching models is beneficial. In Chapter 5, we consider another set of more sophisticated ride-share matching settings…
NPC-based Multi-Source Inverters for Multimode DC Rail Traction Systems

The need for decarbonisation has increased the interest in alternative propulsion systems for light rail vehicles, including fuel cells, batteries, and supercapacitors. These sources and storage devices can also be used in combination with an external supply to enable operation on both electrified and non-electrified tracks. In traditional architectures, the sources are connected via DC/DC converters to a common DC-link that feeds the motor drives. This paper addresses a new configuration where an NPC-based multi-source inverter is used for the integration of the DC sources to the traction motors in a single stage. Firstly, a thorough analysis of the converter’s operation is carried out with reference to its state-of-art control. The conditions for full control of the DC sources and traction motors over the entire vehicle speed profile are derived. Secondly, a novel modulation technique is proposed to complement the baseline control and enable the stationary charging of the energy storage from the electrified line through the converter. Thus, the multi-source inverter can be operated to match all the functionalities of a conventional multimode architecture, with the advantage of reduced number of power converters. Validations are carried out by means of simulations and extensive experiments on a laboratory test bench.
Remote Work and Innovation During this Covid-19 Pandemic: An Employers’ Challenge

The ongoing COVID-19 pandemic is rapidly transforming the remote work culture of many organizations. The demand for online work-from-home has significantly increased during this pandemic. Though it has a significant advantage in eliminating travel time and positively impacting the environment and productive family time, some organizations raise the alarm over the new work style patterns. We discuss some organizational survey results and perspective employees permanently working from home. Some responses have a solid negative relationship on how the work from home affects their organization's innovative culture and work habits. But at the same time, some have expressed positive views and show a strong promise of a cultural shift with sustainable growth. Furthermore, we analyse the present and future pandemic era and how the C-level executives at each organization take the challenge forward to get maximum returns in this competitive global marketplace.