Miracle-dz/UniFAR-FTUs huggingface dataset:
Assaying activity-dependent arteriole and capillary responses in brain slices

Abstract. Significance Neurovascular coupling (NVC) is the process that increases cerebral blood flow in response to neuronal activity. NVC is orchestrated by signaling between neurons, glia, and vascular cells. Elucidating the mechanisms underlying NVC at different vascular segments and in different brain regions is imperative for understanding of brain function and mechanisms of dysfunction. Aim Our goal is to describe a protocol for concurrently monitoring stimulation-evoked neuronal activity and resultant vascular responses in acute brain slices. Approach We describe a step-by-step protocol that allows the study of endogenous NVC mechanisms engaged by neuronal activity in a controlled, reduced preparation. Results This ex vivo NVC assay allows researchers to disentangle the mechanisms regulating the contractile responses of different vascular segments in response to neuronal firing independent of flow and pressure mediated effects from connected vessels. It also enables easy pharmacological manipulations in a simplified, reduced system and can be combined with Ca2+ imaging or broader electrophysiology techniques to obtain multimodal data during NVC. Conclusions The ex vivo NVC assay will facilitate investigations of cellular and molecular mechanisms that give rise to NVC and should serve as a valuable complement to in vivo imaging methods.
Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.
Wireless Photometry Prototype for Tri-Color Excitation and Multi-Region Recording

Visualizing neuronal activation and neurotransmitter release by using fluorescent sensors is increasingly popular. The main drawback of contemporary multi-color or multi-region fiber photometry systems is the tethered structure that prevents the free movement of the animals. Although wireless photometry devices exist, a review of literature has shown that these devices can only optically stimulate or excite with a single wavelength simultaneously, and the lifetime of the battery is short. To tackle this limitation, we present a prototype for implementing a fully wireless photometry system with multi-color and multi-region functions. This paper introduces an integrated circuit (IC) prototype fabricated in TSMC 180 nm CMOS process technology. The prototype includes 3-channel optical excitation, 2-channel optical recording, wireless power transfer, and wireless data telemetry blocks. The recording front end has an average gain of 107 dB and consumes 620 μW of power. The light-emitting diode (LED) driver block provides a peak current of 20 mA for optical excitation. The rectifier, the core of the wireless power transmission, operates with 63% power conversion efficiency at 13.56 MHz and a maximum of 87% at 2 MHz. The system is validated in a laboratory bench test environment and compared with state-of-the-art technologies. The optical excitation and recording front end and the wireless power transfer circuit evaluated in this paper will form the basis for a future miniaturized final device with a shank that can be used in in vivo experiments.
Lessons from the COVID-19 epidemic in Hubei, China: Perspectives on frontline nursing

Background The emergence of COVID-19 has been an ordeal for nurses worldwide. It is crucial to understand their experiences at the frontline, attempt to allay their concerns, and help inform future pandemic response capabilities. Aims To explore nurses’ lived experiences at the frontline in order to identify and address their concerns and help enhance future responses to infectious disease outbreaks. Methods A qualitative study was carried out. Semi-structured interviews were conducted with 60 registered nurses who came to Hubei from different parts of China to care for patients with COVID-19. Interviews were audio-recorded and transcribed verbatim for thematic analysis. Results Six major themes emerged: emotional turmoil due to personal and professional concerns, quality issues with personal protective equipment and associated physical discomfort, witnessing and managing patient distress, readiness of emergency response mechanisms in the health system, collective community awareness and preparedness, and heightened professional pride and confidence in future epidemic control. Discussion Nurses were placed in challenging and unfamiliar situations to deal with unexpected and unpredictable events which caused considerable psychological and physical distress. Support in the form of government edicts, hospital management policies, community generosity and collegiality was highly welcomed by the nurses. Policy makers and managers should ensure that nurses are provided with the support and resources necessary for dealing with large-scale infectious disease outbreaks. Priority should be given to risk assessment, infection prevention and control, and patient and staff health and safety.
START-UP COMPANY? GET YOUR ERP SYSTEM ASAP!”

Enterprise Resource Planning (ERP) systems are increasingly being implemented in organizations around the world. Scholars and practitioners consider the ERP system to be one of the most important technological products in an organization. Such systems have the potential to support organizations in their business operations and business growth, and can provide powerful solutions for integrating business processes. While there are a number of studies on ERP system implementation and use in general, little is known about the ERP experience of newly established companies. This exploratory study thus contributes to the growing literature on ERP implementation by studying a large, newly established company. The study applied a qualitative case-study approach to draw from the experiences of a Palestinian company that implemented an ERP system before starting business operation. Our findings suggest that new ventures can experience fewer challenges in realizing business benefits because they can more easily adopt business processes that match the software features. New ventures do not have entrenched business practices, historical business processes, or persistent culture, factors that have been found to impede realization of ERP benefits. This study recommends that new ventures, especially those who have adequate resources and expect to consistently grow in the market, should consider implementing ERP systems in the early stages, because such systems can help in establishing business operations and can support business growth. Further, many of the known barriers that obstruct benefits from ERP systems do not seem to occur in newly established firms.
Physical Activity and Sedentary Time in Pregnancy: An Exploratory Study on Oxidative Stress Markers in the Placenta of Women with Obesity

Regular moderate-to-vigorous physical activity (MVPA) and reduced sedentary time (ST) improve maternal glucose metabolism in pregnancy. More MVPA and less ST outside pregnancy increase antioxidant capacity, hence, are beneficial in preventing oxidative stress. The placenta is the first line of defense for the fetus from an adverse maternal environment, including oxidative stress. However, effects of MVPA and ST on oxidative stress markers in the placenta are unknown. The purpose of this study was to assess the association of MVPA and ST in pregnancy with oxidative stress markers in placentas of overweight/obese women (BMI ≥ 29 kg/m2). MVPA and ST were objectively measured with accelerometers at <20 weeks, 24–27 and 35–37 weeks of gestation. Using linear Bayesian multilevel models, the associations of MVPA and ST (mean and changes) with mRNA expression of a panel of 11 oxidative stress related markers were assessed in 96 women. MVPA was negatively correlated with HSP70 mRNA expression in a sex-independent manner and with GCLM expression only in placentas of female fetuses. ST was positively associated with HO-1 mRNA expression in placentas of male neonates. None of the other markers were associated with MVPA or ST. We speculate that increasing MVPA and reducing ST attenuates the oxidative stress state in placentas of obese pregnant women.
Application of the Time-Domain Signal Analysis for Electrical Appliances Identification in the Non-Intrusive Load Monitoring

The paper presents a novel method for non-intrusive appliances identification. It can be used for energy load disaggregation in a smart grid. The approach identifies changes in the state of the particular appliance by measuring and processing the common supply current signal. Analysis of the instantaneous changes in the aggregated current on the output of the analyzed circuit in the power network is exploited here. The signal is processed using the time alignment of the current and voltage signals samples represented in the array form. The scheme includes filtering, event detection and identification, which is performed by comparing parameters of the detected event against previously determined signatures of monitored appliances. The analysis is performed in the time domain; therefore (unlike other existing methods), the information contained in the original signal is not lost. The approach was tested in the laboratory designed specifically for this purpose. All tests have been conducted with up to 12 appliances operating at the same time in the single power supply circuit. The measurement setup was developed and used to record appliances’ switching on/off events. During tests, 2300 events for devices were recorded. Collected data were processed to identify particular devices with the accuracy of 98.8% and macro-averaged F-score measure of 0.9874. High identification accuracy was achieved despite the high number of devices operating in the background.
Recognition of fruits and vegetables with similar‐color background in natural environment: A survey

Fruit images collected by picking robots in natural environments have problems such as uneven lighting, complex backgrounds, occlusion of branches and leaves, and overlapping fruits and vegetables, which greatly increases the difficulty for picking robots to accurately identify target fruits and vegetables. Meanwhile, most fruits and vegetables have similar‐color backgrounds. Compared with the ones with different colors in the background, fruits and vegetables in similar‐color backgrounds are similar to the colors of their leaves and surrounding weeds, which increases the difficulty of identification. Therefore, realizing the accurate identification of fruits and vegetables in similar‐color backgrounds is vital to realize the dynamic monitoring of the growth of fruits and vegetables and intelligent picking, which has important value and application prospects for optimizing plantation management and automated harvesting operations. The work summarized the specific characteristics of fruits and vegetables with the close‐color background and the different processing procedures in the identification process. The following methods have been summarized, for example, image acquisition, image preprocessing, feature extraction, image segmentation, and fruit and vegetable detection in the process, and some methods were compared. Finally, the current research was discussed, and a solution was proposed for the different processing steps of fruit and vegetable recognition in similar‐color backgrounds. Deep learning methods were combined with some traditional methods to identify fruits and vegetables with close‐color background, which provides references for further research in various aspects.
Magnetic Field Modelling of a Soft Three-Axis Force Sensor

This paper describes the modelling of a soft three axis force sensor. The sensor has a cylindrical cantilever beam made of silicone rubber that compress and bend when normal and tangential forces are applied. The displacement of the beam’s end is calculated by measuring the change of the magnetic field emitted by a permanent magnet embedded in the soft beam. Spring theory and bending theory, are used to calculate the normal and tangential force components. The normal forces calculated by the proposed model and the measured values has an error less than 5% validating the analogy of the sensor to a soft cantilever beam under compression and bending. The proposed mathematical model is simple and faster than a finite element model, and accurately represents the non-linear behavior of the sensor’s physical effects to applied loads.
SENSE OF COHERENCE AND SUBJECTIVE WELL-BEING AMONG ADOLESCENTS – THE POTENTIAL IMPACT OF LIVING IN A DORMITORY COMPARED TO LIVING WITH FAMILY

SUMMARY The aim of the study was to analyze the relationship between the sense of coherence (SOC) and subjective well-being (SWB) as a health promoting resource among adolescents living with parents and those living in dormitories. There were 442 adolescent responders, yielding a response rate of 84.3%. The SOC was measured using the Orientation to Life Questionnaire, while SWB was obtained from the Personal Wellbeing Index. There were no significant differences between the group living with parents and the group living in dormitories in SOC (128.3 and 129.4, respectively; p=0.580) and SWB (78.0 and 78.9, respectively; p=0.537). A significant difference was found between the genders. Boys had a higher SOC, both those living with parents (131.7 and 124.9, respectively; p=0.014) and those living in dormitories (136.5 and 124.5, respectively; p=0.001), and a higher SWB when living in dormitories (83.4 and 75.8, respectively; p=0.001). Adolescents with better socioeconomic status had a significantly higher SWB if living with parents (76.7 and 85.5, respectively; p=0.003), whereas no difference was found in the dormitory group (78.5 vs. 83.4; p=0.241). The SOC was strongly and positively associated with SWB (correlation coefficient 0.63; p=0.001) and was a key predictor of adolescent SWB (R2=0.373). These findings may prove helpful in future planning and supportive work in schools and dormitories to improve student health.
SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator

Resistive random-access-memory (ReRAM) crossbar is a promising technique for deep neural network (DNN) accelerators, thanks to its in-memory and in-situ analog computing abilities for vector–matrix multiplication-and-accumulations (VMMs). However, it is challenging for crossbar architecture to exploit the sparsity in DNNs. It is inevitably complex and costly to exploit fine-grained sparsity due to the limitation of the tightly coupled crossbar structure. As a countermeasure, we develop a novel ReRAM-based DNN accelerator, named sparse-multiplication-engine (SME), based on a hardware and software co-design framework. First, we orchestrate the bit-sparse pattern to increase the density of bit-sparsity based on existing quantization methods. Such quantized weights can be nicely generated using the alternating direction method of multipliers (ADMM) optimization during the DNN fine-tuning, which can exactly enforce bit patterns in weights. Second, we propose a novel weight mapping mechanism to slice the bits of the weight across crossbars and splice the activation results in peripheral circuits. This mechanism can decouple the tightly coupled crossbar structure and cumulate the sparsity in the crossbar. Finally, a superior squeeze-out scheme empties the crossbars mapped with highly sparse nonzeros from the previous two steps. We design the SME architecture and discuss its use for other quantization methods and different ReRAM cell technologies. We further propose a workload grouping algorithm and a pipeline to achieve workload balance among crossbar-rows that concurrently execute multiply–accumulate operations to optimize the system latency. Putting all together, with the optimized model, compared with prior state-of-the-art designs, the SME shrinks the use of crossbars up to $8.7\times $ and $2.1\times $ using ResNet-50 and MobileNet-v2, respectively, and achieve average $3.1\times $ speed up with no or little accuracy loss on ImageNet.
Intersecting Art and Technology in Practice : Techne/Technique/Technology

This book focuses on the artistic process, creativity and collaboration, and personal approaches to creation and ideation in making digital and electronic technology-based art. Less interested in the outcome itself—the artefact, artwork or performance—contributors instead highlight the emotional, intellectual, intuitive, instinctive and step-by-step creation dimensions. They aim to shine a light on digital and electronic art practice, involving coding, electronic gadgetry and technology mixed with other forms of more established media, to uncover the practice-as-research processes required, as well as the collaborative aspects of art and technology practice.
Chitosan/Gold Nanoparticles Nanocomposite Film for Bisphenol A Electrochemical Sensing

Bisphenol A (BPA) is considered an endocrine-disrupting compound and can cause toxicological effects, even at low doses. The development of sensitive and reliable sensors that would allow the detection of such contaminant is highly pursued. Herein, we report an electrochemical sensing strategy based on a simple and low-cost nanocomposite film sensor platform for BPA detection. The platform was developed by modifying a fluorine-doped tin oxide (FTO) electrode with layer-by-layer (LbL) films of chitosan (Chi) and gold nanoparticles functionalized with a polythiophene derivative (AuNPs:PTS). The growth of the Chi/AuNPs:PTS LbL films was monitored by UV–Vis spectroscopy. Electrochemical characterization revealed that the three-bilayer film exhibited the highest electrocatalytic performance and differential-pulse voltammetry (DPV) measurements demonstrated that the modified electrode was suitable for BPA detection through a quasi-reversible and adsorption-controlled electrochemical oxidation and reduction process. The developed sensor exhibited a linear response range from 0.4 to 20 μmol L−1, with a detection limit of 0.32 μmol L−1. The sensor showed good reproducibility with relative standard deviations of 2.12% and 3.73% to intra- and inter-electrode, respectively. Furthermore, the platform demonstrated to be suitable to detect BPA in real water samples, as well as selective for BPA detection in solutions with 100-fold excess of common interfering compounds.
Topology optimisation of structures exposed to large (non-linear) deformations

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Association between Abnormal Lipid Levels and Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves vital organs of the body. Studies have shown that abnormal lipids may be involved in the pathogenesis of SLE. Hence, the aim of this study was to evaluate lipid profiles in lupus patients. This retrospective cross-sectional study evaluated 136 SLE patients who were referred to the Rheumatology Clinic of Rafsanjan from October 2015 to September 2018. The data for the SLE disease activity index (SLEDAI) and demographic information of all patients were entered in a researcher-created checklist, and serum lipid profiles were measured in serum samples. The SLEDAI score of patients was 13.8 ± 5.9. Age had a significantly positive correlation with cholesterol ( r = 0.224, p value = 0.009) and LDL ( r = 0.256, p value = 0.003) levels as well as significantly negative correlation with HDL levels ( r = -0.489, p value = 0.023). Lipid profiles of patients with different levels of education showed no significant difference ( p value = 0.174). In recently diagnosed patients, SLEDAI had a significantly positive correlation with cholesterol ( r = 0.489, p value = 0.002) and LDL levels ( r = 0.418, p value = 0.009) as well as a significantly negative correlation with HDL levels ( r = -0.381, p value = 0.037). No significant correlation was observed between TG level and SLEDAI ( p value = 0.114, r = 0.19). There was no significant difference in the SLEDAI score between subjects using lipid-lowering drugs and those without such treatment ( p value = 0841). It seems that abnormal lipid levels are common in patients with SLE, and there is an association between abnormal lipids and SLEDAI.