Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly sensitive hybrid optical receiver with a compact 1.4 GHz linear transimpedance amplifier in 55 nm CMOS

Abstract. This work presents a highly sensitive hybrid-integrated optical receiver with a custom designed linear transimpedance amplifier (TIA). The choice of the circuit and diode technology, considering the impact of process parameters on the optical sensitivity and the input referred noise current, are elaborated. The TIA has been designed in a 55-nm complementary metal oxide semiconductor process and was combined with a commercial InGaAs/InP PIN-diode. Measurements resulted in a transimpedance of 9.2 kΩ and a bandwidth of 1.4 GHz. The optical sensitivity of the hybrid receiver is −27.45 dBm for 2 Gbps, with a wavelength of 1550 nm and a bit error rate of 10 − 9. The input referred root mean square (RMS) noise current results in 110 nA. The fabricated chip has an area of 410 μm × 410 μm and a power consumption of 31 mW at a 1 V supply voltage. The performance of the designed TIA is able to match other designs used in high sensitivity applications such as continuous variable quantum key distribution or optical wireless communication, while consuming significantly less power and having a smaller chip area.
On the relativistic Doppler Effects and high accuracy velocity determination using GPS

The NAVSTAR Global Positioning System (GPS) is a satellite-based radionavigation system designed for positioning, velocity determination and timing (PVT). The relative movement between a GPS receiver and a GPS satellite causes the received signal frequency to differ from its nominal frequency due to Doppler effects. This frequency difference, an observable in GPS measurements, is referred to as the Doppler shift. However, the Doppler shift is biased by the inherent error in the receiver clock. Since velocities of GPS satellites are known, the velocity of a user can be determined through observing four or more satellites, similar to GPS positioning. When the GPS selective availability (SA) was activated, errors imposed on the ephemeris and satellite clocks significantly affected the accuracy of both GPS positioning and velocity determination. The removal of SA has enabled a significant improvement on the accuracy of both GPS satellite orbits and clocks. As a result, velocity accuracy at sub-centimeter per second level is achievable for standalone GPS users if all the errors associated with the Doppler observables are corrected for properly. This paper overviews the developments in precise velocity determination and investigates all error sources associated with the Doppler measurement. The properties of errors in the Doppler shift are analysed and the methods to eliminate or mitigate these errors are discussed. The relativistic errors such as the orbit eccentricity and Sagnac effects are derived and formulated in easy forms for correction. Algorithms for modeling the atmosphere delay rates are also presented. A satellite Earth-Centered-Earth-Fixed (ECEF) velocity determination method is also proposed for real-time applications using the broadcast ephemeris. It is concluded that real-time velocities in millimeters per second level are achievable if the error correction schemes provided are used.
Viewpoint Planning for Range Sensors Using Feature Cluster Constrained Spaces for Robot Vision Systems

The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that require the consideration of various system constraints and model uncertainties. Hence, to address some of the challenges, our previous work outlined the computation of valid viewpoints as a geometrical problem and proposed feature-based constrained spaces (C-spaces) to tackle this problem efficiently for acquiring one feature. The present paper extends the concept of C-spaces to consider multi-feature problems using feature cluster constrained spaces (GC-spaces). A GC-space represents a closed-form, geometrical solution that provides an infinite set of valid viewpoints for acquiring a cluster of features satisfying diverse viewpoint constraints. Furthermore, the current study outlines a generic viewpoint planning strategy based on GC-spaces for solving vision tasks comprising multi-feature scenarios effectively and efficiently. The applicability of the proposed framework is validated on two different industrial vision systems used for dimensional metrology tasks.
Improving Audiology Student Training by Clinical Simulation of Tinnitus: A Glimpse of the Lived Experience of Tinnitus

Purpose: Student audiology training in tinnitus evaluation and management is heterogeneous and has been found to be insufficient. We designed a new clinical simulation laboratory for training students on psychoacoustic measurements of tinnitus: one student plays the role of the tinnitus patient, wearing a device producing a sound like tinnitus on one ear, while another student plays the role of the audiologist, evaluating their condition. The objective of the study was to test this new clinical simulation laboratory of tinnitus from the perspective of the students. Method: This study reports the findings from twenty-one audiology students (20 female and 1 male, mean age = 29, SD = 7.7) who participated in this laboratory for a mandatory audiology class at the Laval University of Quebec. Three students had hearing loss (one mild, two moderate). All students played the role of both the clinician and the patient, alternately. They also had to fill out a questionnaire about their overall experience of the laboratory. Results: The qualitative analysis revealed three main themes: “Benefits of the laboratory on future practice”, “Barriers and facilitators of the psychoacoustic assessment”, and “Awareness of living with tinnitus”. The participants reported that this experience would have a positive impact on their ability to manage tinnitus patients in their future career. Conclusion: This fast, cheap, and effective clinical simulation method could be used by audiology and other healthcare educators to strengthen students’ skills and confidence in tinnitus evaluation and management. The protocol is made available to all interested parties.
Electronic Cigarette Prevalence and Knowledge Among Medical Students in Saudi Arabia and Bahrain: A Cross-National Study

Background Electronic cigarettes (e-cigarettes and vapour devices) are the most commonly used form of alternative tobacco products (ATPs). The use of these vapour devices has been dramatically increasing worldwide, especially among current and former traditional cigarette smokers. A strong influence that will affect patients’ health attitudes and play a crucial role in tobacco control and smoking cessation are medical students, as they are future physicians. Therefore, in our study, we aimed to determine the prevalence rate of e-cigarettes and the level of knowledge among medical students in Saudi Arabia and Bahrain. Methods We conducted a cross-sectional study of medical students in Saudi Arabia and Bahrain using an online survey. This was distributed through social media platforms such as Twitter, WhatsApp, Telegram, and Facebook. Medical students of all years were included. The questionnaire was adapted from two previous studies. Results The study enrolled 1730 medical students. The majority of the participants did not recommend the use of e-cigarettes as a method for smoking cessation or believed that these types of ATPs lower the risk of cancer in comparison with traditional cigarettes. The data showed a strong association between gender and e-cigarette smoking, with the majority of current smokers being men (n = 184) and experimental smokers being women (n = 800). Moreover, an educational gap was discovered, as few of the students had received an education in their medical school’s curriculum on the use of e-cigarettes. There was a significant association between receiving an education at a medical school and having adequate knowledge of e-cigarettes. Conclusion The increasing number of e-cigarette users among medical students is concerning. Our study showed that students are not receiving a decent education on the use of ATPs during medical school, which urges further adjustment of the curriculum. This will play a huge role in their behaviour and the provision of future treatment plans to patients as physicians.
Long-term effects of COVID-19 on the endocrine system – a pilot case-control study

Background Coronavirus disease 2019 (COVID-19) has permanently changed the world. Despite having been a pandemic for nearly 3 years, the mid- and long-term complications of this disease, including endocrine disorders, remain unclear. Our study aimed to evaluate the lasting effects of COVID-19 on the endocrine system 6 months after initial infection. Methods We compared patients who underwent COVID-19 to age- and sex-matched subjects from a population-based study conducted before the pandemic. We evaluated differences in multiple parameters related to metabolism and the endocrine system including fasting glucose, insulin, lipids, body composition, thyroid stimulating hormone (TSH), free thyroxine (fT4), free triiodothyronine (fT3), anti-thyroglobulin (aTG) and anti-thyroid peroxidase (aTPO) antibodies, prolactin, cortisol, testosterone, and estradiol. Results We found significantly lower levels of fT3 and fT4, accompanied by higher levels of TSH and aTPO antibodies, in COVID-19 survivors. Moreover, we found that patients who underwent SARS-CoV2 infection had higher levels of prolactin and lower levels of testosterone than controls. Interestingly, differences in testosterone levels were observed only in male subjects. We did not detect significant differences in body composition or metabolic and glycemic parameters between cases and controls, except for significantly higher values of the HOMA2-B index in COVID-19 survivors. Conclusion Our study indicates that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection might have long-term consequences on the endocrine system, including the suppressed function of the thyroid gland, prolactin, and male sex hormone secretion. Moreover, we showed that in a 6-month follow-up, COVID-19 had no consequences on glycemic parameters, lipid profiles, liver function, body composition, cortisol levels, and estradiol levels.
Important value index (IVI) and diversity of mangrove vegetation in Aceh Tamiang, Aceh Province

Mangrove ecosystem is one of the unique ecosystems that has high productivity and it grows along the coast of Aceh Province, Indonesia. The mangrove vegetation in Aceh Tamiang District was decreasing due to human exploitation i.e. stems of mangrove vegetation utilized by local communities become charcoal and firewood. These activities have a negative impact on live and growth of mangrove vegetation. Therefore, the purposes of the study are to analyses the important value index (IVI), mangrove species diversity, and to analyses the correlation between substrate characteristics with mangrove density. The research stations determined using the purposive sampling method and each station has three plots as replication. There were 4 research stations located in Seruway, Bandahara, Banda Mulia, and Manyak Paye sub districts. The study reported 12 species of mangrove in the tree’s category, 9 species of saplings, and 8 species of seedlings. The 12 species of mangroves found were Avicennia lanata, A. marina, A. officinalis, Brugeira parviflora, B. sexangula, Ceriops decandra, C. tegal, Lumnitzera recomosa, Nypa fruticans, Rhizopora apiculata, R. stylosa, and Sonneratia alba. The R. apiculata was species commonly found in each sampling location and it had highest IVI for the tree, sapling and seedling categories with the value of 207.24, 300, and 200, respectively. The average of diversity index was 1.56 categorized in the medium category. The moment Pearson correlation showed there was no significant correlation between the physical-chemical water parameters and substrate with the density of mangrove where Psig0.05. Keywords:Mangrove vegetationImportant value indexDensityDiversityAceh Tamiang
Perceptual Soft End-Effectors for Future Unmanned Agriculture

As consumers demand ever-higher quality standards for agricultural products, the inspection of such goods has become an integral component of the agricultural production process. Unfortunately, traditional testing methods necessitate the deployment of numerous bulky machines and cannot accurately determine the quality of produce prior to harvest. In recent years, with the advancement of soft robot technology, stretchable electronic technology, and material science, integrating flexible plant wearable sensors on soft end-effectors has been considered an attractive solution to these problems. This paper critically reviews soft end-effectors, selecting the appropriate drive mode according to the challenges and application scenarios in agriculture: electrically driven, fluid power, and smart material actuators. In addition, a presentation of various sensors installed on soft end-effectors specifically designed for agricultural applications is provided. These sensors include strain, temperature, humidity, and chemical sensors. Lastly, an in-depth analysis is conducted on the significance of implementing soft end-effectors in agriculture as well as the potential opportunities and challenges that will arise in the future.
Rheumatic Heart Disease in East Africa: A Systematic Review and Meta-Analysis

Background Despite being a grave problem, there is little information on rheumatic heart disease's prevalence in East Africa. Therefore, the purpose of this systematic review and meta-analysis was to estimate the pooled prevalence of rheumatic heart disease in East Africa. Materials and Methods A computerized systematic search of using multiple database searching engines was performed in search of relevant English articles from the inception of the databases to December 2019. It was done in accordance with the preferred reporting items for systematic review and meta-analysis (PRISMA) standard. The funnel plot was used to assess publication bias. R and RStudio for Windows were used for all statistical analysis. The random-effect model was used for calculating the pooled estimate of the prevalence of rheumatic heart disease. Results The database search retrieved 1073 papers, and 80 articles (78 cross-sectional and two cohort study designs) with a total of 184575 individuals were found to be appropriate for the review. In East Africa, the overall prevalence of rheumatic heart disease was 14.67% (95% CI: 13.99% to 15.35%). In Ethiopia, Uganda, Tanzania, and Sudan, respectively, the subgroup analysis of rheumatic heart disease pooled prevalence was 22% (95% CI: 13% to 36%), 11% (95%t CI: 5% to 20%), 9% (95%t CI: 5% to 16%), and 3% (95%t CI: 1% to 10%), while the pooled prevalence of rheumatic heart disease in adults was 20% (95% CI: 12% to 30%), and in children, it was 4% (95% CI: 2% to 8%). Conclusions From this report, the prevalence of rheumatic heart disease in East Africa is very high, affecting about one in seven people. Therefore, future strategies should emphasize preventive measures at appropriate times to minimize the burden of this type of preventable heart disease.
Dyslexia as Learning Disability: Knowledge, Belief and Approach in Language Teaching

Dyslexia is a common learning disability affecting children all around the globe. A misconception on dyslexia is that they only have difficulties in reading and often write letters backwards. This study aims to investigate the correlation between knowledge on dyslexia and teaching approach as well as the way teaching approach is influenced by the beliefs on dyslexia. The sample was selected through simple random sampling technique and identified primarily by referring to the G*Power Calculation Software. The data collection was through questionnaire where its reliability and validity as well as the analysis were performed via PLS-SEM software. The findings reported significant relationship between the beliefs on dyslexia and teaching approach in language learning. Though respondents have decent knowledge on dyslexia but at the same time they also believe that the teaching approach for students with dyslexia should be tailor-made specifically for dyslexic students, focusing on reading, spelling and phonological skills.
The environmental protection law and the zombie companies – evidence from a quasi-natural experimental method

ABSTRACT This paper takes the public companies as a sample during 2012–2017, using DID analysis to test the relationship between 2015 new ‘Environmental Protection Law’ and zombie companies. The results show that the promulgation of the new environmental protection law has significantly negative with zombie enterprises. The strengthening of environmental regulation has accelerated of transformation and upgrading by assets restructuring and promoted technological innovation, which inhibiting the formation of zombie enterprises. Furthermore, this paper found that the negative relationship between environmental law and zombie companies mainly concentrate in non-state-owned enterprises, small-scale enterprises and enterprises with high regional environmental law enforcement intensity. Moreover, the promulgation of the new environmental law has a significant positive effect on corporate value in the medium and long term. This paper enriches the research literature in the field of zombie enterprises and economic consequences of environmental regulation.
The Dark Side of Automation: Robot and Crime

This study presents the first empirical evidence on the impact of industrial robot adoption on criminal activities, utilizing a comprehensive dataset from more than 2 million court documents in China. We find that a one-standard-deviation increase in robot exposure leads to a 12.8%, a 15.5%, and a 9.1% increase in violent, property, and fraud crimes respectively. These results are likely driven by a decrease in the employment-to-population ratio, an increase in drinking frequency, and the deteriorating mental health of individuals. Finally, we find that unemployment insurance is effective in mitigating the adverse impact of robots on crimes.
Design and Performance Analysis of a Nonlinear Magnetic Levitation System Using PID Controller Optimized With COOT Algorithm

Recent growth in magnetic levitation can be attributed to its ability to minimize friction and disturbance in industries, transportation, aerospace, biomedicine, and magnetic bearings. Due to the magnetic levitation system’s nonlinear and unstable nature, control engineers found it exceedingly challenging to design a stabilizing controller. The magnetic levitation system is abbreviated as a maglev system. Using the integral square error criterion, a newly developed metaheuristic algorithm named the COOT algorithm is used to optimize the PID controller parameters. The performance of the proposed algorithm is evaluated using simulation and hardware with several kinds of reference trajectories and compared to the performance of other algorithms, such as the genetic algorithm and the whale optimization algorithm. Based on simulation and hardware results, it was determined that the proposed algorithm performed well with less settling time, rise time, and integral square error.
A Linear Strain-Free Matching Algorithm for Twisted Two-Dimensional Materials

As nano-electronic technology makes electronic devices gradually microscopic in size and diversified in function, obtaining new materials with superior performance is the main goal at this stage. Interfaces formed by adjacent layers of material in electronic devices affect their performance, as does the strain caused by lattice mismatch, which can be simulated and analyzed by theoretical calculations. The common period of the cell changes when the van der Waals (vdW) material is twisted. Therefore, it is a significant challenge to determine the common supercell of two crystals constituting the interface. Here. we present a novel cell matching algorithm for twisted bilayer vdW materials with orthogonal unit cells, where the resulting common supercell remains orthogonal and only angular strains exist without linear strains, facilitating accuracy control. We apply this method to 2-Pmmn twisted bilayer borophene. It can automatically find the resource-allowed common supercell at multiple rotation angles or fix the rotation angle to find the proper accuracy.
CloudDenseNet: Lightweight Ground-Based Cloud Classification Method for Large-Scale Datasets Based on Reconstructed DenseNet

Cloud observation serves as the fundamental bedrock for acquiring comprehensive cloud-related information. The categorization of distinct ground-based clouds holds profound implications within the meteorological domain, boasting significant applications. Deep learning has substantially improved ground-based cloud classification, with automated feature extraction being simpler and far more accurate than using traditional methods. A reengineering of the DenseNet architecture has given rise to an innovative cloud classification method denoted as CloudDenseNet. A novel CloudDense Block has been meticulously crafted to amplify channel attention and elevate the salient features pertinent to cloud classification endeavors. The lightweight CloudDenseNet structure is designed meticulously according to the distinctive characteristics of ground-based clouds and the intricacies of large-scale diverse datasets, which amplifies the generalization ability and elevates the recognition accuracy of the network. The optimal parameter is obtained by combining transfer learning with designed numerous experiments, which significantly enhances the network training efficiency and expedites the process. The methodology achieves an impressive 93.43% accuracy on the large-scale diverse dataset, surpassing numerous published methods. This attests to the substantial potential of the CloudDenseNet architecture for integration into ground-based cloud classification tasks.
Boosting Short Text Classification by Solving the OOV Problem

In the field of natural language processing, text classification has received a lot of attention. Compared with long texts, short texts have fewer words and lack contextual semantic information. Existing approaches enrich short text information by linking the external knowledge graph, but they ignore the out-of-vocabulary (OOV) problem during entity linking, especially when dealing with domain-oriented data, which has some rare words or domain-specific nouns. In this article, to alleviate the OOV problem caused by linking the external knowledge graph(KG), we propose a domain knowledge graph and entity complementation strategy to improve the performance of short text classification. Specifically, the external knowledge graph is used to enrich the information of short texts. The self-build domain knowledge graph is used to solve the problem of entities failing to link to the external knowledge graph. Finally, we conduct experiments on various datasets: 1. a labeled Chinese electronic domain dataset; 2. an open-source dataset to test the performance of our algorithm in different data distribution scenarios. The results demonstrate our dual knowledge graph model outperforms the state-of-the-art short text classification methods, especially when the OOV problem is severe.