Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitigation of cocaine-mediated mitochondrial damage, defective mitophagy and microglial activation by superoxide dismutase mimetics

ABSTRACT Although cocaine exposure has been shown to potentiate neuroinflammation by upregulating glial activation in the brain, the role of mitophagy in this process remains an enigma. In the present study, we sought to examine the role of impaired mitophagy in cocaine-mediated activation of microglia and to determine the ameliorative potential of superoxide dismutase mimetics in this context. Our findings demonstrated that exposure of mouse primary microglial cells (mPMs) to cocaine resulted in decreased mitochondrial membrane potential, that was accompanied by increased expression of mitophagy markers, PINK1 and PRKN. Exposure of microglia to cocaine also resulted in increased expression of DNM1L and OPTN with a concomitant decrease in the rate of mitochondrial oxygen consumption as well as impaired mitochondrial functioning. Additionally, in the presence of cocaine, microglia also exhibited upregulated expression of autophagosome markers, BECN1, MAP1LC3B-II, and SQSTM1. Taken together, these findings suggested diminished mitophagy flux and accumulation of mitophagosomes in the presence of cocaine. These findings were further confirmed by imaging techniques such as transmission electron microscopy and confocal microscopy. Cocaine-mediated activation of microglia was further monitored by assessing the expression of the microglial marker (ITGAM) and the inflammatory cytokine (Tnf, Il1b, and Il6) mRNAs. Pharmacological, as well as gene-silencing approaches aimed at blocking both the autophagy/mitophagy and SIGMAR1 expression, underscored the role of impaired mitophagy in cocaine-mediated activation of microglia. Furthermore, superoxide dismutase mimetics such as TEMPOL and MitoTEMPO were shown to alleviate cocaine-mediated impaired mitophagy as well as microglial activation. Abbreviations: 3-MA: 3-methyladenine; Δψm: mitochondrial membrane potential; ACTB: actin, beta; AIF1: allograft inflammatory factor 1; ATP: adenosine triphosphate; BAF: bafilomycin A1; BECN1: beclin 1, autophagy related; CNS: central nervous system; DNM1L: dynamin 1 like; DMEM: Dulbecco modified Eagle medium; DAPI: 4,6-Diamidino-2-phenylindole; DRD2: dopamine receptor D2; ECAR: extracellular acidification rate; FBS: fetal bovine serum; FCCP: Trifluoromethoxy carbonylcyanide phenylhydrazone; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; IL1B: interleukin 1, beta; IL6: interleukin 6; ITGAM: integrin subunit alpha M; MAP1LC3B: microtubule-associated protein 1 light chain 3 beta; mPMs: mouse primary microglial cells; MRC: maximal respiratory capacity; NFKB: nuclear factor kappa B; NLRP3: NLR family pyrin domain containing 3; NTRK2: neurotrophic receptor tyrosine kinase 2; OCR: oxygen consumption rate; OPTN: optineurin; PBS: phosphate buffered saline; PINK1: PTEN induced putative kinase 1; PRKN: parkin RBR E3 ubiquitin protein ligase; ROS: reactive oxygen species; siRNA: small interfering RNA; SQSTM1: sequestosome 1; TNF: tumor necrosis factor
Self-supervised Contrastive Learning Approach for Bearing Fault Diagnosis with Rare Labeled Data

Data-driven intelligent fault diagnosis methods based on Deep Learning algorithms have been widely studied in recent years. These methods can help reduce costly breakdowns. However, most of such deep-learning methods are supervised, which need numerous labeled data for model training. Learning from just a few labeled examples while making the best use of a large amount of unlabeled data is the target we aim to achieve. In this paper, we innovatively introduce the unsupervised learning method for fault diagnosis. We construct a deep learning structure using the typical contrastive learning method MoCo and a linear classifier. Our structure consists of the encoder network based on ResNet-18 and a simple linear classifier. Experiments are made on the CRWU dataset. The model based on unsupervised features can reach 75.86% accuracy using only a few labeled data, in comparison with the traditional supervised method at 75.86% on average. The use of unsupervised learning also improves the generalization ability of the model.
Static, Dynamic, and Signal-to-Noise Analysis of a Solid-State Magnetoelectric (Me) Sensor with a Spice-Based Circuit Simulator

Modeling the non-electrical processes by equivalent electrical circuits is a widely known and successfully used technique in research and development. Although finite element methods software development has supplanted electrical analogy techniques due to greater accuracy and intuitiveness in recent decades, the modeling of physical processes based on analogies has several advantages in some cases. Representation of physical processes in the form of lumped circuits and graphs allows researchers to estimate the system with an alternative view, use standardized methods for solving electrical circuits for non-electrical systems, and, most importantly, allows us to use electrical circuit simulators with their unique capabilities. Of particular interest for using the analogy technique are systems that include electronic components along with components belonging to other physical domains, such as mechanical, thermal, magnetic, and others. A solid-state magnetoelectric (ME) sensor equipped with a charge amplifier is proposed in this study as an example of analysis using the equivalent electrical circuit and simulating these circuits using SPICE-based circuit simulators. Sensor analysis is conducted with an emphasis on noise budgeting and optimizing the sensor’s signal-to-noise ratio and resolution. In addition, the steady state, the phasor, and transient types of analyses were employed to study the static and dynamic behavior of the system. Validation of the model using analytical calculations and comparison with experimental data demonstrated superior results.
Potassium hydroxide-treated walnut shell residue biochar for wastewater treatment: phenol adsorption and mechanism study

Using walnut shell as raw material and potassium hydroxide as an activating agent, the walnut shell carbon (denoted as WSC) was prepared for phenol adsorption. The prepared biocomposite adsorbent structure was investigated using N 2 adsorption–desorption analysis, Fourier-transform infrared spectroscopy, X-ray diffraction and scanning electron microscopy techniques. Adsorption efficiency of the prepared samples were investigated in various conditions such as activator ratio, initial phenol concentration, activation temperature, pH and adsorption reaction temperature. Also the kinetic and thermodynamic studies were carried out. The Brunauer–Emmett–Teller sur- face of the best WSC is 435.98 m 2 g –1 and the maximum pore volume is 0.299 cm 3 g –1 , also it has a layered structure and porosity. When the mass ratio of WSC to KOH is 1:0.1, the amount of WSC (700°C, 2 h) is 2.0 g L –1 and the initial concentration of phenol is 20 mg L –1 , the adsorption properties show that the prepared WSC has good adsorption performance with the phenol removal rate of 98.78% in 60 min. The kinetic study illustrates that the phenol adsorption on WSC fits the non-linear pseudo-first-order. It indicates that the phenol adsorption on WSC is accompanied by mainly physical adsorption.
Procalcitonin as a Predictive Tool for Death and ICU Admission among Febrile Neutropenic Patients Visiting the Emergency Department

Background and Objectives: Risk stratification tools for febrile neutropenia exist but are infrequently utilized by emergency physicians. Procalcitonin may provide emergency physicians with a more objective tool to identify patients at risk of decompensation. Materials and Methods: We conducted a retrospective cohort study evaluating the use of procalcitonin in cases of febrile neutropenia among adult patients presenting to the Emergency Department compared to a non-neutropenic, febrile control group. Our primary outcome measure was in-hospital mortality with a secondary outcome of ICU admission. Results: Among febrile neutropenic patients, a positive initial procalcitonin value was associated with significantly increased odds of inpatient mortality after adjusting for age, sex, race, and ethnicity (AOR 9.912, p < 0.001), which was similar, though greater than, our non-neutropenic cohort (AOR 2.18, p < 0.001). All febrile neutropenic patients with a positive procalcitonin were admitted to the ICU. Procalcitonin had a higher sensitivity and negative predictive value (NPV) in regard to mortality and ICU admission for our neutropenic group versus our non-neutropenic control. Conclusions: Procalcitonin appears to be a valuable tool when attempting to risk stratify patients with febrile neutropenia presenting to the emergency department. Procalcitonin performed better in the prediction of death and ICU admission among patients with febrile neutropenia than a similar febrile, non-neutropenic control group.
Swarm Crawler Robots Using Lévy Flight for Targets Exploration in Large Environments

This study tackles the task of swarm robotics, where robots explore the environment to detect targets. When a robot detects a target, the robot must be connected with a base station via intermediate relay robots for wireless communication. Our previous results confirmed that Lévy flight outperformed the usual random walk for exploration strategy in an indoor environment. This paper investigated the search performance of swarm crawler robots with Lévy flight on target detection problems in large environments through a series of real robots’ experiments. The results suggest that the swarm crawler robots with Lévy flight succeeded in the target’s discovery in the indoor environment with a 100% success rate, and were able to find several targets in a given time in the outdoor environment. Thus, we confirmed that target exploration in a large environment would be possible by crawler robots with Lévy flight and significant variances in the detection rate among the positions to detect the outdoor environment’s target.
DEVELOPMENT OF ANDROID-BASED “MBARENGI” STATISTICS E-MODULE AS AN INNOVATION FOR STATISTICS LEARNING MEDIA WITH HYBRID LEARNING

The learning process is closely related to the interaction between educators and students. In order to facilitate the learning process, educators are required to make learning more innovative in order to be able to encourage students to study hard and be able to follow the learning process well. One of the innovations that can be done in the learning process is innovation in learning media. Learning media is one of the components of learning that has an important role in teaching and learning activities, especially in the transition after the Covid 19 pandemic. The use of smartphones can be one of the innovations of learning media by using Android-based e-modules. This research is development research or called Research and Development (R&D) using the ADDIE development model (Analyze, Design, development, Implementation, and Evaluation). The Android-based "MBARENGI" Statistics E-Module was validated by material experts, learning media experts, and tested on a limited scale sample. The results of the validation of material experts on the aspect of content material are 91.5% and on the language aspect are 93.2%. The results of media expert validation on the aspect of content quality are 92.3%, on design and audio aspects are 94.4% and the interaction and feedback aspects are 92.3%. In the test results, student responses obtained an average result are 88.8% which stated that the Android-based "MBARENGI" Statistics E-Module was feasible to be used in the learning process.
Who succeeds and who fails? Exploring the role of background variables in explaining the outcomes of L2 language tests

This study explores whether and to what extent the background information supplied by 10,155 immigrants who took an official language test in Norwegian affected their chances of passing one, two, or all three parts of the test. The background information included in the analysis was prior education, region (location of their home country), language (first language [L1] background, knowledge of English), second language (hours of second language [L2] instruction, L2 use), L1 community (years of residence, contact with L1 speakers), age, and gender. An ordered logistic regression analysis revealed that eight of the hypothesised explanatory variables significantly impacted the dependent variable (test result). Several of the significant variables relate to pre-immigration conditions, such as educational opportunities earlier in life. The findings have implications for language testing and also, to some extent, for the understanding of variation in learning outcomes.
Randomness-E-cient Sampling within NC 1

We construct a randomness-e‐cient averaging sampler that is computable by uniform constantdepth circuits with parity gates (i.e., in uniform AC 0 [']). Our sampler matches the parameters achieved by random walks on constant-degree expander graphs, allowing us to apply a variety expander-based techniques within NC 1 . For example, we obtain the following results: † Randomness-e‐cient error-reduction for uniform probabilistic NC 1 ;TC 0 ;AC 0 ['] and AC 0 : Any function computable by uniform probabilistic circuits with error 1=3 using r random bits is computable by circuits of the same type with error ‐ using r + O(log(1=‐)) random bits. † An optimal bitwise †-biased generator in AC 0 [']: There exists a 1=2 ›(n) -biased generator G : f0;1g O(n) ! f0;1g 2 n for which poly(n)-size uniform AC 0 ['] circuits can compute G(s)i given (s;i) 2 f0;1g O(n) £ f0;1g n . This resolves a question raised by Gutfreund and Viola (Random 2004). † uniform BP ¢ AC 0 µ uniform AC 0 =O(n). Our sampler is based on the zig-zag graph product of Reingold, Vadhan and Wigderson (Annals of Math 2002) and as part of our analysis we give an elementary proof of a generalization of Gillman’s Chernofi Bound for Expander Walks (FOCS 1994).
Acute stress – but not aversive scene content – impairs spatial configuration learning

ABSTRACT Contextual learning pervades our perception and cognition and plays a critical role in adjusting to aversive and stressful events. Our ability to memorise spatial context has been studied extensively with the contextual cueing paradigm, in which participants search for targets among simple distractor cues and show search advantages for distractor configurations that repeat across trials. Mixed evidence suggests that confrontation with adversity can enhance as well as impair the contextual cueing effect. We aimed to investigate this relationship more systematically by devising a contextual cueing task that tests spatial configuration learning within complex visual scenes that were emotionally neutral or negative (Study 1) and was preceded by the Maastricht Acute Stress Test (MAST) or a no-stress control condition (Study 2). We demonstrate a robust contextual cueing effect that was comparable across negative and neutral scenes (Study 1). In Study 2, acute stress disrupted spatial configuration learning irrespective of scene valence and endogenous cortisol reactivity to stress. Together with the emerging evidence in the literature, our findings suggest that spatial configuration learning may be subject to complex regulation as a function of spatial or temporal proximity to a stressor, with potential implications for the development of stress-related psychopathology.
Light field imaging for computer vision: a survey

Light field (LF) imaging has attracted attention because of its ability to solve computer vision problems. In this paper we briefly review the research progress in computer vision in recent years. For most factors that affect computer vision development, the richness and accuracy of visual information acquisition are decisive. LF imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays, acquiring complete three-dimensional (3D) scene information. LF imaging technology improves the accuracy of depth estimation, image segmentation, blending, fusion, and 3D reconstruction. LF has also been innovatively applied to iris and face recognition, identification of materials and fake pedestrians, acquisition of epipolar plane images, shape recovery, and LF microscopy. Here, we further summarize the existing problems and the development trends of LF imaging in computer vision, including the establishment and evaluation of the LF dataset, applications under high dynamic range (HDR) conditions, LF image enhancement, virtual reality, 3D display, and 3D movies, military optical camouflage technology, image recognition at micro-scale, image processing method based on HDR, and the optimal relationship between spatial resolution and four-dimensional (4D) LF information acquisition. LF imaging has achieved great success in various studies. Over the past 25 years, more than 180 publications have reported the capability of LF imaging in solving computer vision problems. We summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.
Distribution-free performance bounds with the

Gascuel, O. and G. Caraux, Distribution-free performance bounds with the resubstitution error estimate, Pattern Recognition Letters 13 (1992) 757-764. Two distribution-free upper bounds are given for the true error rate of a classifier, using the resubstitution error estimate. These bounds apply when the classifier is selected from a finite decision rule set. Both improve a bound proposed by Vapnik (1982). One of them is in a way optimal, while however presenting the disadvantage to be not analytic and requiring to be computed numerically for a given situation. A quantitative comparison of these bounds is provided, with realistic parameter values taken from classification trees and histogram discrimination rules.
The design and optimization of the down-lead system for a novel 400 kV composite

—This paper presents systematic research of a grounding down-lead design and its optimization for a novel Y-shaped composite pylon. A grounding down-lead inside the cross-arm is proposed as a potential grounding method. The transient response to lightning surges is modeled in PSCAD/EMTDC for a flash of lightning striking at the tip of the pylon. Aiming at the characteristic of the pylon structure, we propose theoretical formulas to calculate the surge impedance of the inclined down-lead circumscribed by composite materials. Besides, potential multi-factors affecting BFR such as the configuration as well as the length of the down-lead, the pylon span, the dielectric constant of the filling material, the electromagnetic propagation speed of the lightning, and the capacitances between down-lead and phase conductors are investigated, after which the grounding lead system of the pylon and filling materials are determined. Afterwards, the applicability of the multi-down-lead system to increase critical current ( I c ) is discussed considering the lightning current capacity and the corona generation. Finally, we verify the insulation of the down-lead system. Compared with that of traditional Eagle and Donau towers, the backflashover rate (BFR) of the Y-shaped pylon with an optimized down-lead system is lower than that of traditional ones.
An Introduction of a Modular Framework for Securing 5G Networks and Beyond

Fifth Generation Mobile Network (5G) is a heterogeneous network in nature, made up of multiple systems and supported by different technologies. It will be supported by network services such as device-to-device (D2D) communications. This will enable the new use cases to provide access to other services within the network and from third-party service providers (SPs). End-users with their user equipment (UE) will be able to access services ubiquitously from multiple SPs that might share infrastructure and security management, whereby implementing security from one domain to another will be a challenge. This highlights a need for a new and effective security approach to address the security of such a complex system. This article proposes a network service security (NSS) modular framework for 5G and beyond that consists of different security levels of the network. It reviews the security issues of D2D communications in 5G, and it is used to address security issues that affect the users and SPs in an integrated and heterogeneous network such as the 5G enabled D2D communications network. The conceptual framework consists of a physical layer, network access, service and D2D security levels. Finally, it recommends security mechanisms to address the security issues at each level of the 5G-enabled D2D communications network.
Internet-of-Things-Enabled Smart Bed Rail for Application in Hospital Beds

This article presents an atypical offline based LoRaWAN application for use in hospital settings, where the ability to maintain network connectivity during internet connection disruption is paramount. A prototype bed rail is demonstrated, providing advanced functionality compared to traditional bed rails. The manufactured prototype provides data to a nurses station reliably and operates under battery backup. The power consumption of the system under different transmission intervals was tested, allowing appropriate battery sizing for different applications to be specified accurately. It is expected that a single LoRaWAN gateway will be able to cover bed rails across an entire modern hospital, allowing minimal infrastructure cost to implement the device or application in a rapidly deployed field hospital.
Oncogenic KRAS signaling activates mTORC1 through COUP‐TFII‐mediated lactate production

Oncogenic signals contribute to enhanced glycolysis and mTORC1 activity, leading to rapid cell proliferation in cancer. Regulation of glycolysis and mTORC1 by PI3K/Akt signaling is well established, but how KRAS‐induced MEK signaling regulates these pathways remains poorly understood. Here, we report a role for MEK‐driven lactate production in mTORC1 activation in KRAS‐activated cells. KRAS/MEK‐induced upregulation of the chicken ovalbumin upstream promoter transcriptional factor II (COUP‐TFII) increases the expression of lactate dehydrogenase A (LDHA), resulting in lactate production and mTORC1 activation. Further, lactate inhibits the interaction of TSC2 and Rheb, leading to the cellular activation of mTORC1 irrespective of growth factor stimulation. These findings suggest that COUP‐TFII is a novel oncogenic mediator, connecting KRAS signaling and glycolysis, and leading to mTORC1 activation and cellular growth.
Characteristics of Sleep Patterns in Adolescents: Comparisons between Saudi Arabia and the UK

There are concerns regarding sleep deprivation among adolescents, especially with mounting evidence for the importance of sleep during puberty, and its effects on health and families. The present study aimed to characterise sleep in typical development (TD) adolescents in Saudi Arabia, and compare their sleep profiles to TD adolescents in the UK, to evaluate sleep patterns in adolescents in Saudi Arabia, and to examine the relationship between sleep patterns and the use of social media in both groups. Findings from the current study reported a shorter sleep duration for the Saudi Arabia group than in previous studies and the UK group, which may be attributed to the lack of sleep hygiene practised in Saudi Arabia. Multiple analysis of variance results found significant differences in daytime sleepiness (p < 0.001) and a preference for morningness/eveningness (p < 0.001) between Saudia Arabia and UK adolescents. Statistically significant negative correlations (p > 0.05) between the duration of social media usage and sleep duration were found in both the Saudi Arabia and UK adolescents, where a lower number of sleep hours was observed with a higher duration of social media use. This study fills a gap in the research of sleep in Saudi Arabia in adolescents, and offers important insights on the comparison in sleep habits between Saudi Arabia and UK adolescents.