Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a 4-DOF Piezoelectric Micro-gripper

： To reduce the complexity of micromanipulation system, a 4-DOF piezoelectric micro-gripper is proposed. Firstly, a 4-DOF piezoelectric micro-gripper is designed using the piezoelectric bimorph actuators. The gripper could bring displacements both in the gripping direction and the vertical direction. The gripper is composed of two unimorphs which is designed as clamp shape. The driving electrodes of the gripper are fabricated on non adhesive surface of each unimorph. The driving electrodes on the unimorph are mutually insulated and aligned with each other. Secondly, the relationships between the displacement and the geometric parameters of the finger, as well as driving voltage are deduced based on the bending theory of piezoelectric cantilevers. Then the static and dynamic characterizations of the optimized gripper are analyzed using ANSYS. Finally, the static and the dynamic performances of the micro-gripper are tested experimentally. The results show that: at the driving voltage of 60 V, the displacements of the left and right finger in the gripping direction are 25.7 μm and 26.1 μm, respectively; the displacements of the left and right finger in the vertical direction are 33.8 μm and 32.8 μm, respectively. The displacements of two fingers have good repeatability. In the gripping direction and the vertical direction, the natural frequencies of the gripper are 2.35 kHz and 0.62 kHz, respectively. The response time of the micro-gripper in the gripping direction and vertical to the gripping direction are both 0.23 s at the step voltage of 15 V.
Nano - patents and Literature Frequency as Statistical Innovation Indicator for the use of Nano - porous Material in Three Major Sectors: Medicine, Energy and Environment

The statistical analysis of patents in specific areas can be an important tool for the evaluation of trends and advancements in specific research fields. Patenting is generally considered to be steered by commercial needs; hence it primarily concentrates on research results that are expected to have an important economic value. Patent data can be utilized to conduct comparative studies and trend analysis. This paper examines the granted patents from the United States Patent and Trademark office (USPTO) and the European Patent Office (EPO), in regards to the creation and/or use of nanoporous materials. The patents found were categorized by subject, and those belonging in the areas of Medicine, Energy or Environment were further analysed. The study also includes statistics about quality/value indicators, such as forward and backwards citations and references, age, family and materials used, as well as statistical data on the occurrences in literature of the materials studied, as found via a Scopus database search. The goal of this paper is to identify current trends and opportunities in these areas, and try to find possible gaps between the current reality and important societal needs. The identified trends and opportunities could be used by the industry as well as researchers, in order to adjust investment strategies, improve and potentially commercialize the corresponding patented applications.
Improving inferences and predictions of species environmental responses with occupancy data

Occupancy models represent a useful tool to estimate species distribution throughout the landscape. Among them, MacKenzie et al.’s model (2002, MC), is frequently used to infer species environmental responses. However, the assumption that detection probability is homogeneous or fully explained by covariates may limit its performance. Species should be more easily observed at sites with a higher number of individuals. We simulated data following occupancy model (RN) that accounts for abundance‐driven heterogeneous detection and two variants with overdispersion in the detection probability and local abundances. Then, we compared the performance of the MC model against that of RN. In addition to model misspecifications, insufficient information in data (i.e. infrequent detections) can limit our ability to detect existing effects with affordable sampling designs. To deal with this source of error, we extended RN approach to a community‐level joint species model (RN‐JSM), where species responses and detectability depended on their traits and phylogeny. Then, we tested RN‐JSM performance in simulated and out‐of‐sample field data. High abundance‐driven heterogeneity in detection (i.e. common and secretive species) limited the ability of the MC model to quantify covariate effects; especially, when the number of visits was low. Both models (MC and RN), often failed to detect existing effects when data were overdispersed. Moreover, the RN model consistently lacked sufficient power when analysing data from uncommon species (even when simulations and model specifications perfectly matched). This problem was solved by our RN‐JSM, which yielded more precise and accurate estimates of species environmental responses. Increased accuracy in rare species held when the RN‐JSM was tested with real and out‐of‐sample datasets. In the light of our results, we propose: (i) for common and secretive species analyse occupancy data with the RN model and prioritize revisiting sites; (ii) for species that may have overdispersed detectability or local abundances (e.g. with correlated behaviours or occurring in clusters), apply RN extensions that account for this extra‐variation (e.g. Poisson‐beta or zero‐inflated models). Finally, (iii) for uncommon species (mean abundances <1), whenever possible, gather data at the community level and apply joint species modelling techniques.
Robust control of vortex‐induced vibration in flexible bridges using an active tuned mass damper

The tuned mass damper (TMD) is widely used to mitigate vortex‐induced vibration (VIV) that approximates harmonic vibration in bridges. Robust performance is, however, still a significant concern in the VIV mitigation of bridges, especially when using a TMD with a small mass ratio. This study presents a study to apply an active tuned mass damper (ATMD) to control VIV in bridges. The control algorithm is independent of bridge parameters and can achieve real‐time tuning to the bridge motion by a few measurements. An adaptive TMD, obeying the parameter‐independent algorithm, is developed to improve its robust performance when exposed to uncertainty in the natural frequency of the bridge, and then, the ATMD is used to implement such an adaptive TMD. The ATMD control using the LQG algorithm is used as a comparison to illustrate the advantage of the parameter‐independent algorithm in the VIV mitigation of bridges. The effect of the control‐structure interaction on the control effect is also discussed. Demonstration of the method on a numerical simulation of a long‐span box‐girder bridge confirms the potential superiority of the ATMD control using the parameter‐independent algorithm in the VIV mitigation of bridges.
Age-dependent Aedes mosquito resistance profiling and mortality rate to repeated insecticides exposure in Western region, Saudi Arabia

Background Little is documented on Aedes aegypti age-dependent role on different resistance mechanisms to repeated insecticides exposures. The study examined the age-dependence of mortality rate and genetic resistance in two mechanistically pyrethroid resistant mosquito strains exposed once or repeatedly at different ages. Methods WHO bioassays and real time polymerase chain reaction (qPCR) were performed to ascertain their association between age-dependent exposures related mortality rate and single/repeated resistance in the Jeddah and Makkah. Candidate genes of interest (CYP9J7, CYP9J27, CYP9J26, AAEL006953, CYP9P450, AAEL006013) were assessment. Results Age dependent and exposure duration had a significant effect on the survival of the Jeddah and resistant Cayman. Our results showed that in a single exposure assays, age had no significant effect on mortality in the Cayman strain (χ2=2.76, df=1, P=0.097), but there was significantly increased mortality in the Jeddah strain younger age (χ2=5.46, df=1, P=0.02), but not statistically significant at older age. In the multiple exposure assay, GLiM analysis showed a significant strain, day and strain*day interaction indicating mortality rate is influenced by the strain or day (which also corresponds to age). The Jeddah strain showed generally lower survival,, there was a highly significant association of survival with repeated exposures in the Jeddah strain (χ2=43.6, df=1, P=4.1×10E-11) and the Cayman strain (χ2=12.5, df=1, P=0.0004). Mortality rate correlated statistically and significantly with the number of days of exposure in the Cayman strain (Spearman rank correlation ρ=-0.77, P=0.01), but in the Jeddah strain it was not statistically significant (ρ= -0.42, P=0.23). After repeated insecticide exposure, the AAEL006013 was statistically and significantly over-expressed compared to the control (P=0.03). Conclusion To the best of our knowledge, this is one of the first research on age and exposure linked genomic and bioassay on field Ae. aegypti in Jeddah, KSA. The study showed that repeated exposure to pyrethroids reduced the Aedes mosquito population mortality rate. This suggests that there is indeed increasing age-dependent resistance or survival with multiple exposure high-doses of same or repeated insecticide, thus indicating the need to rethink on integrated vector control policy and interventions and technical assistance in the Kingdom.
Language Models Learn Sentiment and Substance from 11,000 Psychoactive Experiences

Drugs like entactogens and psychedelics appear poised to enter clinical psychiatry, however we lack a unified framework for quantifying the changes in conscious awareness optimal for treatment. We address this need using transformers (i.e. BERT) and 11,821 publicly-available, natural language testimonials from Erowid. First, we predicted 28 dimensions of sentiment across each narrative, validated with clinical psychiatrist annotations. Secondly, another model was trained to predict biochemical (pharmacological and chemical class, molecule name, receptor affinity) as well as demographic (sex, age) information from the testimonials. Thirdly, canonical correlation analysis (CCA) linked the 52 drugs’ affinities for 61 receptor subtypes with word usage across the testimonials, revealing 11 latent receptor-experience factors each mapped to a 3D cortical atlas of receptor gene-expression. Together, these 3 machine learning methods elucidate a neurobiologically-informed, temporally-sensitive portrait of drug-induced subjective experiences. These models are mutually confirmatory, pointing to an underlying structure of psychoactive experience dominated by the distinction between the lucid and the mundane, but also sensitive to effects unique to individual drugs. For example, MDMA was singularly linked to mid-experience swelling of “Love”, potent psychedelics like DMT, and 5-MeO-DMT were associated with “Mystical Experiences”, while other tryptamines were associated with an emotional constellation of “Surprise”, “Curiosity” and “Realization”. Applying these models to real-time biofeedback (e.g. EEG) with zero-shot learning that tunes the sentimental trajectory of the experience through changes in audiovisual outputs, practitioners could guide the course of therapeutic sessions, maximizing benefit and minimizing harm for patients.
An Improved Sine Wave Histogram Test Method for ADC Characterization

This paper presents a modified version of the sine wave histogram test for analog-to-digital converter (ADC) characterization. To accurately estimate the transition levels, the input signal has to fulfill strict conditions, which are coherent sampling and uniform distribution of the phases. Noncoherent sampling of the sine wave leads to systematic errors in the transition level estimation, while the nonuniform distribution of the phases increases the variance of the results using the original sine wave histogram test method. The source of the errors is the improper modeling of the histogram of the measured signal. This paper shows that the true histogram of the measured sine wave can be reconstructed by estimating the phases of the sampled signal. It is shown that integrating this information into the estimation of the transition levels can significantly decrease the effect of noncoherent sampling, thus the ADC can be characterized accurately even if the conditions are not fulfilled. The proposed method is verified on both simulated and real measurement data.
Manipulation de nanofils de silicium à partir de nano robots

Nous presentons dans cet article une proposition de travaux pratiques sur la manipulation de nanofils de silicium individuels a partir de nano-robots pilotes par ordinateur. Ces nano-robots sont installes dans l’enceinte d’un microscope electronique a balayage. Le controle des nano-robots se fait par ordinateur via un module electronique d’interface.
Graphene Nanoribbon as Potential On-Chip Interconnect Material—A Review

In recent years, on-chip interconnects have been considered as one of the most challenging areas in ultra-large scale integration. In ultra-small feature size, the interconnect delay becomes more pronounced than the gate delay. The continuous scaling of interconnects introduces significant parasitic effects. The resistivity of interconnects increases because of the grain boundary scattering and side wall scattering of electrons. An increased Joule heating and the low current carrying capability of interconnects in a nano-scale dimension make it unreliable for future technology. The devices resistivity and reliability have become more and more serious problems for choosing the best interconnect materials, like Cu, W, and others. Because of its remarkable electrical and its other properties, graphene becomes a reliable candidate for next-generation interconnects. Graphene is the lowest resistivity material with a high current density, large mean free path, and high electron mobility. For practical implementation, narrow width graphene sheet or graphene nanoribbon (GNR) is the most suitable interconnect material. However, the geometric structure changes the electrical property of GNR to a small extent compared to the ideal behavior of graphene film. In the current article, the structural and electrical properties of single and multilayer GNRs are discussed in detail. Also, the fabrication techniques are discussed so as to pattern the graphene nanoribbons for interconnect application and measurement. A circuit modeling of the resistive-inductive-capacitive distributed network for multilayer GNR interconnects is incorporated in the article, and the corresponding simulated results are compared with the measured data. The performance of GNR interconnects is discussed from the view of the resistivity, resistive-capacitive delay, energy delay product, crosstalk effect, stability analysis, and so on. The performance of GNR interconnects is well compared with the conventional interconnects, like Cu, and other futuristic potential materials, like carbon nanotube and doped GNRs, for different technology nodes of the International Technology Roadmap for Semiconductors (ITRS).
Recent advances in digital health interventions for substance use disorders

Purpose of review The purpose of this review is to provide an update of the recently published randomized controlled trials in the field of digital health interventions for substance use disorders. Recent findings Over the past 2 years, five cannabis-specific and seven polysubstance-focused randomized controlled trials were published. No studies were found that focused on opioid or psychostimulant use disorders. Most studies examined feasibility but were underpowered to assess effectiveness. Given the optimistic results of the studies in regards to feasibility more fully powered trials should be conducted. In addition, the literature is in need for an increased focus on comorbidity and outcome standardization. Summary Although the number of studies targeting new target groups, technologies and new delivery settings has increased – future studies should consider the identified gaps and suggestions to further strengthen the evidence of digital interventions targeting substance use disorders.
Digital approaches to continuing care

Purpose of review To provide an update of studies on the effectiveness of digital and telephonic approaches to providing remote continuing care for substance use disorders. Recent findings Effective continuing care can be provided via smartphone apps, text messaging, interactive voice response, and structured telephone counseling. The remote continuing care interventions with the strongest evidence of efficacy are the Addiction Comprehensive Health Enhancement Support System app and Telephone Monitoring and Counseling. Positive effects for these intervention on drinking outcomes in patients with alcohol use disorders were replicated in a recent randomized controlled study. Summary Continuing care is widely believed to be an important component of treatment for substance use disorders, especially for sustaining positive outcomes. However, many individuals do not attend clinic-based continuing care, due to a variety of reasons, including competing work and family responsibilities, disabilities, transportation challenges, and recently the COVID-19 pandemic. Remote continuing care, provided via smartphone apps, text messaging, and various telephonic approaches, has been shown to be effective, and could be used to provide continuing care to patients who would otherwise not receive it. Further work is needed to determine how to effectively combine more traditional continuing care with newer digitized and telephonic approaches.
Testing Weak Form Market Eﬃciency for Emerging Economies: A Nonlinear Approach

In this paper, we address weak form stock market efficiency of Emerging Economies, by testing whether the price series of these markets contain unit root. Nonlinear behavior of stock prices is well documented in the literature, and thus linear unit root tests may not be appropriate in this case. For this purpose, we employ the nonlinear unit root test procedure recently developed by Kapetanios et al. (2003) and nonlinear panel unit root test Ucar and Omay (2009) that has a better power than standard unit root tests when series under consideration are characterized by a slower speed of mean reversion. Large power gains are achieved through combining cross-sectional information and nonlinear estimation techniques in computing unit root tests. The results of ADF and PP indicate that Bulgarian, Greek, Hungarian, Polish, Romanian, Russian, Slovenian and Turkish stock markets are weak form efficient, while the results of nonlinear unit root test implies that Russian, Romanian and Polish stock markets are not weak form efficient. Moreover, the linear panel unit root test suggest that this group as all efficient where as nonlinear panel unit root test suggest as a group they are not efficient.
Privacy and Security in Pervasive and Ubiquitous Computing

— With ubiquitous computing, individuals are always surrounded by technology, which has become an essential part of their daily routines. Ubiquitous computing, also known as pervasive computing, is a concept where computing is available anytime and anywhere. It is supported using any device, any location, and any format. With technology being intertwined in human lives, the problem arises when we start to discuss the user's privacy and security in pervasive/ubiquitous computing environments. There are many ways in which a user's privacy and security can be at risk. This paper will examine these privacy and security issues and discuss techniques that could solve these problems. Our research results show that the average of finding a pseudonym in our controlled experiment is 0.012694%. With these results, we conclude that the possibility of tracking a single pseudonym consistently in an area of a half square mile is virtually impossible.
A Review Paper on Graphene Coated Fibres

Graphene is now known as a super material because of its fascinating physical properties. Due to a great scope of research, it has now become a center of at-traction of research scholars in physics, chemistry as well as materials science to study and explore its potential applications. In this paper, a brief review is presented on the various graphene synthesis methods and a short introduction of different types of fibres is discussed. Various studies have been carried out to obtain graphene coating on different fibres and observe the changes in their physical and chemical properties. This paper also provides the different types of coating methods used to form graphene layer on the fibres discussed.
Quad-Band Wearable Slot Antenna with Low SAR Values for 1.8 GHz DCS, 2.4 GHz WLAN and 3.6/5.5 GHz WiMAX Applications

In this paper, a quad-band wearable slot antenna with low specific absorption rate (SAR) is presented. By cutting an inverted V-shaped slot with its arms further extended towards the center of the circular patch, multiple resonant modes of the antenna can be excited to operate on 1.8 GHz DCS, 2.4 GHz WLAN and 3.6/5.5 GHz WiMAX bands. The measured peak gains and impedance bandwidths are about 4.91/7.84/2.58/4.12 dBi and 320/60/80/180 MHz for the 1.8/2.4/3.6/5.5 GHz bands respectively. The SAR of the proposed antenna has been measured using a three layer human tissue model. The estimated SAR values at all the resonant frequencies are well below the threshold limit of 2W/kg, which ensures its viability for wearable applications. In order to approximate different parts of the human body, the SAR values have been estimated for three surface sizes, 120 × 120 mm2, 220 × 220 mm2 and 320 × 320 mm2, of the human tissue model, and results are compared. Frequency detuning of the proposed antenna due to bending along x, y and x-y planes has also been carried out and discussed. Further, on arm effect on the antenna performance is investigated, and results are presented. The simulated and measured results are in good agreement, which validates the use of proposed wearable antenna in DCS/WLAN/WiMAX bands.
DC side voltage control consideration for single phase shunt Active Power Filter for harmonic and reactive power compensation

Shunt Active Power Filter (APF) is widely used to address the harmonic pollution created by nonlinear loads in power system. The APF consists of dual loop, inner current control responsible for shaping the output current of the APF, while DC side voltage control loop is accountable for power balancing. The APF current control is highly demanding due to non-sinusoidal reference and considered vital to obtain desired compensation performance. DC side voltage control too has a pronounced impact on APF’s compensation characteristics, if not properly considered. This paper evaluates the various factors that have impact on the performance of the DC side voltage control. A moving average filter is used to eliminate the even harmonics present on capacitor voltage as a result of harmonic compensation before it is fed to comparator and voltage controller. The paper also presents the brief description and design of DC side components of single phase APF. A comparison between PI based and Fuzzy Logic based DC side voltage control is carried out. The analysis and performances are evaluated with simulation results.