Miracle-dz/UniFAR-FTUs huggingface dataset:
An X-band high power amplifier module package using selectively anodized aluminum substrate

In this paper, we made a high power amplifier module package using a selectively anodized aluminum substrate for the X-band radar T/R modules. The proposed solution of package is based on thick anodized aluminum oxide (Al2O3) layers and power chips mounted on aluminum for an effective heat sink. The fabricated high power amplifier module has a maximum output power of 39.49 dBm and maximum gain of 32 dB over 9 - 10 GHz frequency band. This package method can be further contributed to decreasing cost, reducing module size and managing thermal problem for the microwave high power T/R modules.
Torque ripple minimization of switched reluctance machines through current profiling

The paper presents a novel method of profiling the phase currents to minimize the torque ripple of a switched reluctance machine (SRM). The method is a combination of machine design and control algorithm. The minimization is accomplished through three steps. The first step is to design a machine which has symmetric torque characteristics with a maximum flat portion. The second step is to find the required current profile through simulation. The third step is fine tuning the profile through coupled simulation of the machine in the finite element and the dynamic controller in the Matlab/Simulink environments. The coupled simulation takes into consideration of the nonlinearities, electrical loss, magnetic loss, and mutual coupling.
Real Time Video Analytics for Object Detection and Face Identification using Deep Learning

-Video analytics is growing field in the machine learning and deep learning domain. This paper proposed the model that is capable of performing video analytics at large scale and faster pace and generated the appropriate inference on time. It include the detail of the algorithm for the automation in video analytics personalized cameras, security and Surveillance system using deep learning. This include much optimized algorithm for identification of the faces. The second module is consisting of object identification using deep learning and libraries that are capable of identifying 3 million object i.e. COCOAPI. Video Summarization is a technique introduced to increase the speed of investigation. The Module produced much optimized summary of video.
An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for Securing Internet-of-Things Applications

This paper presents the first hardware implementation of the datagram transport layer security (DTLS) protocol to enable end-to-end security for the Internet of Things (IoT). A key component of this design is a reconfigurable prime field elliptic curve cryptography (ECC) accelerator that is 238<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> and 9<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> more energy-efficient compared to software and state-of-the-art hardware, respectively. Our full hardware implementation of the DTLS 1.3 protocol provides 438<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> improvement in energy-efficiency over software, along with code size and data memory usage as low as 8 and 3 KB, respectively. The cryptographic accelerators are coupled with an on-chip low-power RISC-V processor to benchmark applications beyond DTLS with up to two orders of magnitude energy savings. The test chip, fabricated in 65-nm CMOS, demonstrates hardware-accelerated DTLS sessions while consuming 44.08 <inline-formula> <tex-math notation="LaTeX">$\mu \text{J}$ </tex-math></inline-formula>/handshake and 0.89 nJ/byte of the encrypted data at 16 MHz and 0.8 V.
On Buffer-Aided Relaying for the Two-Hop Full Duplex Relay Channel with Self-Interference

In this paper, we investigate the fading two-hop full-duplex (FD) relay channel with self- interference, which is comprised of a source, an FD relay impaired by self-interference, and a destination, where a direct source-destination link does not exist. For this channel, we propose two buffer-aided relaying schemes with adaptive reception-transmission at the FD relay for the cases when the source and the relay both perform adaptive-rate and fixed-rate transmission, respectively. The proposed buffer-aided relaying schemes enable the FD relay to adaptively select to either receive, transmit, or simultaneously receive and transmit in a given time slot based on the qualities of the receiving, transmitting, and self-interference channels; a degree-of-freedom unavailable without buffer-aided relaying. Our numerical results show that significant performance gains are achieved using the proposed buffer-aided relaying schemes compared to conventional FD relaying, where the FD relay is forced to always simultaneously receive and transmit, and to buffer-aided half-duplex relaying, where the half-duplex relay cannot simultaneously receive and transmit. The main conclusion of this work is that FD relaying systems without buffer-aided relaying miss-out on significant performance gains.
Rational re-design of Lactobacillus reuteri 121 inulosucrase for product chain length control

Fructooligosaccharides (FOSs) are well-known prebiotics that are widely used in the food, beverage and pharmaceutical industries. Inulosucrase (E.C. 2.4.1.9) can potentially be used to synthesise FOSs from sucrose. In this study, inulosucrase from Lactobacillus reuteri 121 was engineered by site-directed mutagenesis to change the FOS chain length. Three variants (R483F, R483Y and R483W) were designed, and their binding free energies with 1,1,1-kestopentaose (GF4) were calculated with the Rosetta software. R483F and R483Y were predicted to bind with GF4 better than the wild type, suggesting that these engineered enzymes should be able to effectively extend GF4 by one residue and produce a greater quantity of GF5 than the wild type. MALDI-TOF MS analysis showed that R483F, R483Y and R483W variants could synthesise shorter chain FOSs with a degree of polymerization (DP) up to 11, 10, and 10, respectively, while wild type produced longer FOSs and in polymeric form. Although the decrease in catalytic activity and the increase of hydrolysis/transglycosylation activity ratio was observed, the variants could effectively synthesise FOSs with the yield up to 73% of substrate. Quantitative analysis demonstrated that these variants produced a larger quantity of GF5 than wild type, which was in good agreement with the predicted binding free energy results. Our findings demonstrate the success of using aromatic amino acid residues, at position D418, to block the oligosaccharide binding track of inulosucrase in controlling product chain length.
Online Estimation of the Condensate Load in Dryer Cylinders During Section Starting

A “condensate load” (condensate in % of a totally full cylinder) over 1% accumulated inside the dryer cylinders of a paper machine is likely to produce a drive overload, eventually increasing the acceleration time or even producing an overload trip. This paper proposes and evaluates a confident online condensate estimation algorithm that gives updated information at preset speeds and when the transition to the rimming stage is detected. The experimental evaluation performed on a 500-mm-diameter cylinder, with condensate load between 0.5% and 25%, confirmed the ability of the algorithm to give accurate estimations within 0.5% intervals of condensate loads. The developed algorithm is a useful tool for the operators, allowing them to take the appropriate decisions according to the severity of the condensate accumulation detected.
Food inflation nowcasting with web scraped data

In this paper we evaluate the ability of web scraped data to improve nowcasts of Polish food inflation. The nowcasting performance of online price indices is compared with aggregated and disaggregated benchmark models in a pseudo realtime experiment. We also explore product selection and classification problems, their importance in constructing web price indices and other limitations of online datasets. Therefore, we experiment not only with raw indices, but also with several approaches to include them into model-based forecasts. Our findings indicate that the optimal way to incorporate web scraped data into regular forecasting is to include them in simple distributed-lag models at the lowest aggregation level, combine the forecasts and aggregate them using statistical office methodology. We find this approach superior to other benchmark models which do not take online information into account.
The Right to Education for Children with Disabilities from the Earliest Age/Pravo na odgoj i obrazovanje djece s teškoćama od najranije dobi

Abstract The right to education constitutes a fundamental human right and is the focus of numerous international agreements, conventions, as well as scientific and expert research. Grounded in a human rights perspective, this study aims to understand the involvement of children with disabilities in early education programs. The participants—parents of children with disabilities (N=10)—reported challenges faced while enrolling their children with disabilities in early education institutions, including insufficient support or even denied enrolment. Study participants also emphasized challenges extending beyond enrolment: children’s stays in daycare had been limited, children were insufficiently included in extracurricular activities, and parents encountered organizational challenges in securing financing for special needs assistants. While satisfied with the personal competencies of teachers, participants were dissatisfied with the teachers’ professional skills and were equally dissatisfied with the performance of the professional team. Some participants recounted discrimination against their children. In conclusion, these narratives reveal “vulnerabilities” of the early education system. Given the importance of educational inclusion for children with disabilities, this topic requires continued attention. Key words: children with disabilities; Croatia; early education; inclusion. --- Sažetak Pravo na obrazovanje temeljno je ljudsko pravo i u sredistu je brojnih međunarodnih ugovora, konvencija, znanstvenih i strucnih istraživanja. Ovaj rad temelji se na modelu ljudskih prava i cilj mu je istražiti ukljucenost djece s teskocama u programe ranog odgoja i obrazovanja. Sudionici istraživanja – roditelji djece s teskocama u razvoju (N = 10) opisuju izazove s kojima se suocavaju prilikom upisa djeteta s teskocama u predskolske ustanove, izražavaju nedostatak podrske kod upisa ili cak nemogucnost upisa svog djeteta u predskolsku ustanovu. Također, sudionici nailaze na izazove unutar samog vrtica. Djetetu se ogranicava boravak u skupini, smatraju da postoji nedovoljna ukljucenost djeteta s teskocama u aktivnosti, a naglasavaju organizacijske poteskoce vezane uz osiguranje rada asistenta. Sudionici su zadovoljni osobnim kompetencijama odgojiteljica, ali su nezadovoljni njihovim profesionalnim kompetencijama, bas kao sto svoje nezadovoljstvo iskazuju i u vezi s radom strucnog tima. Neki su sudionici spomenuli diskriminaciju djece. Zakljucno, ti iskazi otkrivaju "ranjivosti" ranog obrazovnog sustava. S obzirom na važnost ukljucivanja u obrazovanje za djecu s teskocama u razvoju, ova tema zahtijeva stalnu pozornost. Kljucne rijeci: djeca s teskocama u razvoju; Hrvatska; inkluzija; rani odgoj i obrazovanje.
171Yb+ single-ion optical frequency standard at 688 THz

Two <sup>171</sup>Yb<sup>+</sup> single-ion optical frequency standards operating at 688 THz (436 nm) are compared in order to investigate systematic frequency shifts in the sub-Hertz range. In the absence of externally applied perturbations, a mean relative frequency difference of 3.8(6.1)·10<sup>-16</sup> is observed. This agreement is comparable to that of the most accurate comparisons between cesium fountain clocks. Using a femtosecond frequency comb generator based on a Er<sup>3+</sup>-doped fiber laser, the frequency of the <sup>171</sup>Yb<sup>+</sup> standard is measured with a relative systematic uncertainty of 3.1·10<sup>-15</sup> and a statistical uncertainty of 0.6·10<sup>-15</sup>.
Measurement of aerosol properties during wintertime in Beijing

Abstract. Severe haze events with exceedingly high-levels of aerosols have occurred frequently in China in recent years, threatening human health and affecting regional and global radiative budget. A better knowledge of aerosol properties during haze events, particularly for those occurring during wintertime, will be helpful for elucidating the haze formation mechanism. In this study, we conducted a field measurement at an urban site in Beijing during January and February of 2015. A suite of aerosol instruments was deployed to measure a comprehensive set of aerosol chemical and physical properties. The haze events in winter, regulated by meteorological conditions, typically start with a new particle formation event and progress in terms of the subsequently continuous growth of the nucleation mode particles to submicron particles over the following multiple days. Particulate organic matters are primarily responsible for producing the nucleation mode particles, while secondary organic and inorganic components jointly contribute to the high aerosol mass observed during haze events. The average effective density and kappa value of ambient particles are approximately 1.37 g cm−3 and 0.25 during the clean days, and 1.42 g cm−3 and 0.4 during the severe haze episodes, respectively, indicating the formation of secondary inorganic species during the development of the severe haze events. Our results reveal that the periodic cycles of severe haze formation in Beijing during wintertime are attributed to the fast secondary aerosol formation due to the high gaseous precursor concentrations and the stagnant air mass, which are analogous to the severe haze events observed during autumn.
Desarrollo y Validación de una Escala para Medir Apoyo Social en Adultos con Perspectiva de Apego

Se desarrollo y valido una escala para evaluar la busqueda, percepcion y experiencia emocional asociadas a la recepcion de apoyo en adultos mexicanos, asi como las creencias que les subyacen. A traves de la tecnica de preguntas abiertas se exploraron las manifestaciones en estas cuatro areas en cincuenta adultos mexicanos. Posteriormente el instrumento fue aplicado a 274 participantes, una serie de analisis factoriales llevados a cabo durante la fase cuantitativa dividieron la totalidad del instrumento en 7 subescalas. La confiabilidad general de la escala fue de . 86. La validez de constructo se probo a traves de la relacion de todos los factores de la nueva escala con las dimensiones de ansiedad y evitacion del apego. Los resultados muestran que la nueva escala se adecua a los modelos teoricos que la sustentan y arroja correlaciones en las direcciones esperadas.
Things and Strings and More: Improving Place Name Disambiguation from Short Texts by Combining Entity Co-Occurrence, Topic Modeling, and Word Embedding

Author(s): Ju, Yiting | Advisor(s): Janowicz, Krzysztof W | Abstract: Place name disambiguation, i.e., toponym disambiguation or toponym resolution, is the task of correctly identifying a place from a set of places sharing a common name. It contributes to a variety of tasks such as knowledge extraction, query answering, geographic information retrieval, and automatic tagging. Disambiguation quality relies on the ability to correctly identify and interpret contextual clues, complicating the task for short texts. Here I propose a novel approach to the disambiguation of place names from short texts that integrates three models: entity co-occurrence, topic modeling, and word embedding. The first model uses Linked Data to identify related entities to improve disambiguation quality. The second model uses topic modeling to differentiate places based on the terms used to describe them. The third model uses word embeddings to uncover the semantic relatedness between places and contexts. I evaluate this approach using a corpus of short texts collected through web scraping, determine the suitable weights for the models, and demonstrate that the combined model, i.e., Things and Strings Model, outperforms benchmark systems such as DBpedia Spotlight, TextRazor, and Open Calais by up to 85% in F-score and 46% in Precision at 1. A web service is built to demonstrate the proposed method and it can be a building block for those applications that need place name recognition and disambiguation.
Photoacoustic Imaging in Gastroenterology: Advances and Needs

Gastroenterologists routinely use optical imaging and ultrasound for the minimally invasive diagnosis and treatment of chronic inflammatory diseases and cancerous tumors in gastrointestinal tract and related organs. Recent advances in gastroenterological photoacoustics represent combination of multispectral and multiscale photoacoustic (PA), ultrasound (US), and near-infrared (NIR) fluorescent imaging. The novel PA endoscopic methods have been evaluated in preclinical models using catheter-based miniature probes either noncontact, all-optical, forward-viewing probe or contact, side-viewing probe combined with ultrasound (esophagus and colon). The deep-tissue PA tomography has been applied to preclinical research on targeted contrast agents (pancreatic cancer) using benchtop experimental setups. The clinical studies engaging human tissue ex vivo have been performed on endoscopic mucosal resection tissue with PA-US tomography system and intraoperative imaging of pancreatic tissue with PA and NIR fluorescence multimodality. These emerging PA methods are very promising for early cancer detection and prospective theranostics. The noninvasive transabdominal examination with PA-US handheld probe has been implemented into clinical trials for the assessment of inflammatory bowel disease. To facilitate translational and clinical research in PA imaging in gastroenterology, we discuss potential clinical impact and limitations of the proposed solutions and future needs.
Subgradient-Based Neural Networks for Nonsmooth Convex Optimization Problems

This paper develops a neural network for solving the general nonsmooth convex optimization problems. The proposed neural network is modeled by a differential inclusion. Compared with the existing neural networks for solving nonsmooth convex optimization problems, this neural network has a wider domain for implementation. Under a suitable assumption on the constraint set, it is proved that for a given nonsmooth convex optimization problem and sufficiently large penalty parameters, any trajectory of the neural network can reach the feasible region in finite time and stays there thereafter. Moreover, we can prove that the trajectory of the neural network constructed by a differential inclusion and with arbitrarily given initial value, converges to the set consisting of the equilibrium points of the neural network, whose elements are all the optimal solutions of the primal constrained optimization problem. In particular, we give the condition that the equilibrium point set of the neural network coincides with the optimal solution set of the primal constrained optimization problem and the condition ensuring convergence to the optimal solution set in finite time. Furthermore, illustrative examples show the correctness of the results in this paper, and the good performance of the proposed neural network.
Drinking practices and alcohol-related problems among Nigerian students

Abstract Background: Alcohol-related problems are increasing among Nigerian University students. However, very few studies have explored the ways in which hazardous drinking practices facilitate these problems in Nigerian University students, aside from quantitative studies focussing on students in South-Western Nigeria. Methods: Drawing on qualitative semi-structured interviews involving students from a South-Eastern Nigerian University, this study begins to address these gaps. The participants were recruited through convenience and snowballing sampling techniques, and the data were analysed thematically. Results: The findings show that 24 out of 31 participants engaged in heavy drinking by consuming between 3 and 9 bottles of beer/stout or flavoured spirits regularly. These heavy drinkers had suffered financial, academic, and health problems. Some lost valuable personal items such as mobile phones, wallets, and money as a result of drinking, while others missed examinations because drinking had rendered them either too ill or had caused them to oversleep and missed the examination. Almost all participants had suffered multiple health-related problems such as hangovers, accidents and injuries, liver enlargement, stomach ache, attempted suicide (under the influence of alcohol), and sex with strangers. Conclusion: Evidence-based public health interventions to address easy alcohol availability and heavy drinking should be implemented in Nigerian Universities.
Development of New Data Acquisition System at Super-Kamiokande for Nearby Supernova Bursts

Super-Kamiokande (SK), a 50-kiloton water Cherenkov detector, is one of the most sensitive neutrino detectors. SK can be used also for supernova observations by detecting neutrinos generated at supernova. In order to improve the performance of the detector for supernovae, we are developing two new features, one for recording all information within one minute and the other for recording calorimetrical information for nearby supernovae. The current SK data acquisition (DAQ) system reads out all the photomultiplier tube (PMT) hits, including the dark noise, and applies software trigger to select events to record. Therefore, the PMT hits caused by very low energy events below the threshold are not stored. Since supernova burst is a very rare phenomenon and details of the burst mechanism are not known yet, all possible data should be recorded without any bias in the trigger system. To accomplish this, we are adding a new feature to the DAQ system to record all the PMT hit information before and after the burst occurs for about one minute. According to the simulation study based on the Livermore model, the neutrino burst from a supernova farther than about 1300 light years can be recorded without loss of data by the current DAQ system. However, if a supernova burst occurred within a few hundreds of light years, the neutrino event rate can be more than 30 MHz and the system can record only about first 20% of the events. To overcome this inefficiency, we are developing a new DAQ system that can handle such high-rate neutrino events. This new DAQ system records the number of hit PMTs in a certain time window with the time stamp, so that we can count the neutrinos and obtain a time profile of the number of neutrinos emitted at the supernova. We will present the implementation of these improvements. The results of the tests with the final prototype before the mass production will be shown.