Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration-Guided Q-Learning

In many challenging reinforcement learning (RL) settings, demonstrations are used to assist with exploration by allowing policies or value functions to directly learn from successful experience. In this work, we explore additional ways to utilize expert demonstrations to expedite training in value-based RL. In particular, we propose Demonstration-Guided Q-Learning (DGQL), an algorithm that noisily re-plays expert demonstrations to guide exploration and enable more efﬁcient Q-value propagation in value-based RL methods. Contrary to common methods that utilize demonstrations in the context of value-based RL, we show that DGQL effectively leverages demonstrations to guide exploration via a replaying curriculum that re-laxes common assumptions in simulated environments. In addition to analyzing the empirical beneﬁts of more efﬁcient value propagation, we show that DGQL is able to scale to difﬁcult vision-based robotic manipulation tasks.
EAWORTHINESS OF N A : ITU ONSERVATION C AVE E NDANGERED C ETACEANS

A 2018 workshop entitled Ex Situ Options for Cetacean Conservation (ESOCC) led to the creation of a sub-group of the International Union for Conservation of Nature (IUCN) Species Survival Commission Cetacean Specialist Group, called the Integrated Conservation Planning for Cetaceans (ICPC). The ICPC has proposed to integrate ex situ measures with in situ efforts in small cetacean conservation plans, including in certain circumstances holding some individual animals in seminatural reserves and/or artificial enclosures (e.g., concrete tanks) and breeding them in captivity. Integrating these ex situ measures into conservation plans has gained supporters as immediate threats (e.g., fishing gear entanglement and habitat loss) continue to impede or prevent the recovery of endangered small cetacean species and populations, leading conservationists to feel a growing sense of urgency regarding their protection.
DISFLUENCY DETECTION FOR A

A computer-implemented method for creating a disfluency translation lattice includes providing a plurality of weighted finite state transducers including a translation model, a language model, and a phrase segmentation model as input, performing a cascaded composition of the weighted finite Corporation state transducers to create a disfluency translation lattice, and storing the disfluency translation lattice to a computer
Physico-chemical characteristics of habitat and morphometric analysis on Barilius bendelisis of bariliine cyprinids in Torsa river of West Bengal, India: A potential area of new research

a good agreement with the report given by Hamilton, Rahman, Jayaram, Shafi and Quaddus [19-22]. But we have observed few variations in characteristics which are very special for the studied species. Meristic characters of the majority bariliines are highly conventional and illustrate small variations, therefore observations were made, therefore, with great care to stay away from errors, to avoid specimen being referred to the incorrect species. Specimen of Barilius bendelisis (Figures 1 and 2). Was collected from Torsa River by using cast net during October 2020 (Figure 1). The colour in fresh specimens was taken before fixation and preservation. All counts and measurements i.e. lateral line scale count, anatomical measurements. Vertebral counts were done by using standard procedures [23-26]. 2 general taxonomy of the Indian bariliine cyprinids in the beam of accessible information. The mean value, the physico-chemical parameters (water temperature-26 o C, pH-7.4, dissolved oxygen-6.8 g/l, etc.) of the habitat was suitable to survive the species. Findings of the result suggests to go for further study to find the huge possibility that the studied species may show cryptic diversity of already reported Barilius bendelisis of this region.
Understanding the Mechanism of Star-Block Copolymers as Nanoreactors for Synthesis of Well-Defined Silver Nanoparticles

Facile and large-scale synthesis of well-defined, thermally stable silver nanoparticles protected by polymer brushes for use in practical applications is still a challenge. Recent work has reported a nanoreactor approach that can be used to synthesize these silver nanoparticles. This approach uses amphiphilic star-block copolymers, which have a hydrophilic core surrounded by a hydrophobic exterior. These polymers thus can serve as the nanoreactors. In this study, we hypothesize that the local high concentration of silver ions in the inner hydrophilic cores of these star-block copolymers facilitates the nucleation and subsequent growth of silver nanoparticles. When all silver nanoparticles nucleate from the cores of the star-block copolymers in solution, the particle size can be controlled by the core size of the polymer. To test this hypothesis, a polyisoprene-b-poly(p-tert-butylstyrene) (PI-b-PtBS) star-block copolymer was functionalized with carboxylic acid groups using a high-efficiency, photo-initiated thiol-ene click reaction. We characterized this modified polymer using proton nuclear magnetic resonance spectroscopy, and the results indicated that ~60% of the double bonds in the polyisoprene block were successfully functionalized with carboxylic acid groups. When silver ions were added to a solution of these functionalized star-block copolymers, the negatively charged carboxylic acid groups would attract the positively charged silver ions. Subsequent reduction of these Ag+ by a tert-butylamine-borane complex at room temperature produced nanosized silver particles. However, transmission electron microscopy images showed that a significant amount of relatively large silver nanoparticles grew outside the star-block copolymer nanoreactors.
The Effectiveness of Cognitive Rehabilitation on Planning and Working Memory of Executive Functions in Cochlear Implanted Children

Background and Aim: Today, hearing loss affects various aspects of executive functions and cognitive rehabilitation is important in increasing planning capacity and working memory. The purpose of this study was to investigate the effectiveness of cognitive rehabilitation on planning and working memory of executive functions in cochlear implanted children. Methods: This study was a semi-experimental clinical trial. Using the purposive sampling method, 24 hearing-impaired children with cochlear implants were randomly divided into two groups: an experimental group (12 subjects) and a control group (12 subjects). The experimental group received 12 treatment sessions based on a protocol of cognitive rehabilitation program for executive functions (spatial planning and working memory), while the control group did not participate in this program. We assessed executive function using the Cambridge Neuropsychological Test Automated Battery (CANTAB), which assessed the Stockings of Cambridge (SOC) and Attention switching task (AST). Results: The results of MANCOVA were shown to be effective at the post-test stage for improving executive function in the experimental group (p≤0.001). But there was no significant difference in stockings of Cambridge problem solve and stockings of Cambridge move 4 between two groups after the intervention. Conclusion: There was a significant increase in spatial planning and spatial working memory of the experimental group. Cognitive rehabilitation can be a useful intervention to improve spatial planning and spatial working memory in cochlear implanted hearing-impaired children. Keywords: Cognitive rehabilitation; executive function; hearing-impaired; cochlear implant
BODY COMPONENTS CHANGES AND DEPRESSION SCORES BEFORE COMPETITIONS AMONG ELITE FEMALE WRESTLERS

Among weight-sports like wrestling where athletes are required to weigh-in before the competitions and their weights are measured; athletes generally lose weight. Athletes who carry out weight loss through sweat room, fluid and food restrictions undergo dehydration. The current study was undertaken to examine body components changes and their depression scores caused by dehydration among the female elite wrestlers. 29 female elite wrestlers who participated in Turkish Inter-University Wrestling Championship were included in the study. Beck ’ s Depression Inventory (BDI) used to determine depression scores of female elite wrestlers; personal information forms that addressed age, height, weight, amount of weight lost before the competition and body components [Tanita BC-418 brand via bioelectrical impedance analysis (BIA)] were administered one hour before weigh-in competition. Data was tested for normality with the Shapiro-Wilk test. The independent Samples T Test was used to compare pairwise group variables that followed a normal distribution. In the current study it has been found statistically significant difference between percentage of body fat, body fat mass, percentage of total body water and depression scores according to weight loss group and non-weight loss group. As a result; it has been found that fat mass is lower and depression scores' is mild degree for female elite wrestlers performing weight loss.
Wireless Hand Rehabilitation System (WHRS)

Loss of motor skills in hand due to several reasons affects daily life in a negative way. Treatment or rehabilitation must be applied in order to reactivate motor skills. Different systems were developed in the rehabilitation process by benefiting from technology. Those systems work as telerehabilitation-based or with external skeleton manipulator. An internet connection is required for telerehabilitation-based systems and a physical therapist must carry out the rehabilitation process for systems with external skeleton manipulator. This shall increase the work load of physical therapist. In this study, it is aimed to decrease the work load of physical therapist and develop a hand rehabilitation system with easier and more flexible usage. With this purpose, a system that consists of three units communicate with each other wirelessly and which could be used even without a physical therapist.
Aeroacoustic computations of tones generated from low mach number cavity flows, using a preconditioned method

The hydrodynamically generated noise produced from flow over cavities includes both broadband and tones. The frequency content and amplitude of the resulting noise is a function of the cavity geometry and the approaching boundary layer. The cavity length to depth ratio (L/D) is an important parameter that governs the characteristics of cavity noise generated. While both of the noise components are important this work will focus on the production of cavity tones. Cavity tones typically have higher sound pressure levels and can propagate over longer distances than the broadband noise. The enhancements to the numerical code shown in this work result in the first non-hybrid tool for the prediction of low speed cavity noise. At moderate subsonic Mach numbers the direct calculation of cavity tones has been performed by numerous researchers using highly accurate spatial and time discretization. However, most researchers that are trying to predict the noise from low Mach number flows take a hybrid approach where the fluid dynamics of the simulation are solved with a computational fluid dynamics (CFD) solver and the acoustics are solved separately. The other solver is often based on Lighthill’s Acoustic Analogy or an asympototic method such as the Expansion about Incompressible Flow (EIF). This work calculates the conservative Navier-Stokes variables to directly predict the cavity tones. The numerical solver CHOPA (Compressible, High-Order Parallel Acoustics) is extended in this work for the accurate and fast calculation of low Mach number cavity flows. A time-derivative preconditioner equalizes the acoustic wave and turbulence convective speeds to allow for a more efficient time step and shorter calculation times. Because the preconditioner destroys the time accuracy of the solution a dual-time step approach is used for the time integration. Other modifications to the code are required to facilitate the proper implementation of the preconditioner: Matrix-based artificial dissipation, buffer zone, and extrapolation boundary condition. An extension by Buelow of Choi-Merkle’s viscous preconditioner is selected for this work.
Additively manu actured AlSi10Mg inherently stable thin and thick-walled lattice with negative Poisson’s ratio

Literature on the mechanical per ormance o additively manu actured (AM) negative Poisson’s ratio (− ) structures has been primarily ocused on beam-based re-entrant structures with chevron crosslinks. The walled variants o this architecture have been shown to exhibit lateral instability. This is where a layered ramework can be advantageous as they provide increased lateral stability. Much less is known regarding the behaviour o such architecture, let alone their thin/thick-walled variants. This study explores the in luence o design parameters namely wall thickness ( ) and angle ( ) on the mechanical per ormance o thin and thick-walled inherently stable − lattices. The design is achieved through conceiving linearly arranged AlSi10Mg re-entrant unit-cells while discarding the traditional chevron crosslinks. The printed prototypes were experimentally tested and response sur ace (RS) models were generated to study the parametric in luence on the elastic modulus (E), compressive strength ( ), ailure strain ( ), − and relative density ( ). The results demonstrate that both thinand thick-walled structures exhibit o -0.108 to -0.257 despite the interaction e ects between and . The elastic modulus can be increased by either increasing or without considering the interaction e ects at 0.3 ≤ ≤ 1 mm and 45° ≤ ≤ 85°. This study presents a new understanding regarding the abrication and per ormance o re-entrant structures by AM.
An Empirical Analysis of Text Summarization Approaches for Automatic Minuting

A signiﬁcant portion of the working population has their mainstream interaction virtually these days. Meetings are being organized and recorded daily in volumes likely exceeding what can be ever comprehended. With the deluge of meetings, it is important to identify and jot down the essential items discussed in the meeting, usually referred to as the minutes . The task of minuting is diverse and depends on the goals, style, procedure, and category of the meeting. Automatic Minut-ing is close to summarization; however, not exactly the same. In this work, we evaluate the current state-of-the-art summarization models for automatically generating meeting minutes. We provide empirical baselines to motivate the community to work on this very timely, relevant yet challenging problem. We conclude that off-the-shelf text summarization models are not the best candidates for generating minutes which calls for further research on meeting-speciﬁc summarization or minuting models. We found that Transformer-based models perform comparatively better than other categories of summarization algorithms; however, they are still far from generating a good multi-party meeting sum-mary/minutes. We release our experimental code at https://github.com/ELITR/ Minuting_Baseline_Experiments .
Auditory Neuropathy Spectrum Disorder in Brown- Vialetto-Van Laere Syndrome

Background and Aim: This study shows the clinical symptoms pertinent to auditory neuropathy spectrum disorder (ANSD) for a 16-year-old girl with Brown-Vialetto-Van Laere Syndrome (BVVL). The results have been followed for six years between 2015 and 2021. The Case: In the present study, auditory test battery including tympanometry, acoustic reflex, pure tone audiometry, transient evoked otoacoustic emissions and auditory brainstem response were utilized and repeated three times during six years. Conclusion: In the first session, the results revealed bilaterally normal transient evoked otoacoustic emissions, absent acoustic reflexes (ipsilateral and contralateral), mild to moderate low tone loss in the pure tone audiometry, no auditory brain stem responses at high stimulus intensities and different polarities and present cochlear microphonic component in single polarities. In the second session, pure tone audiometry showed slight to mild high tone loss but the other tests demonstrated their same results. In the final session, the latter results were repeated. In this comprehensive follow up study, the patient with BVVL demonstrated clinical symptoms of auditory neuropathy spectrum disorder in which auditory system showed an impairment in the auditory temporal synchronization and encoding. Keywords: Brown-Vialetto-Van Laere syndrome; auditory neuropathy spectrum disorder; auditory brainstem response; pure tone audiometry
Book Review: Speech and Language Processing (second edition) by Daniel Jurafsky and James H. Martin

Speech and Language Processing is a general textbook on natural language processing, with an excellent coverage of the area and an unusually broad scope of topics. It includes statistical and symbolic approaches to NLP, as well as the main methods of speech processing. I would rank it as the most appropriate introductory and reference textbook for purposes such as an introductory fourth-year undergraduate or graduate course, a general introduction for an interested reader, or an NLP reference for a researcher or other professional working in an area related to NLP. The book’s contents are organized in an order corresponding to different levels of natural language processing. After the introductory chapter 1, there are five parts:
Comparative Analysis of Women’s Health Living in Villas and those Living in Apartments in Esfahan

In the old city of Esfahan which has been renowned as a garden city, people are growingly moving towards purchasing apartments instead of villas as the prices of land and properties have risen, whereas the historical background of this city demonstrates that people used to live in houses with spacious courtyards which had trees, greenery, and in big ones a pond with little fish. The aim of this study is to examine if there a difference among the health of people who live in apartments and those who live in villas in Esfahan. In order to achieve this, first, the definitions and concepts of mental and physical health, inner peace are mentioned and then the effects of greenery inside houses on the quality of the house and its residents’ feelings and behaviors are analyzed thoroughly. The results indicated that those who live in villas are healthier than those who live in apartments.
Design and Simulation Study of Solar Photovoltaic Array using Simulink Model

— This paper proposes to plan the model of photovoltaic solar cell and simulate it, considering the effect of solar irradiations and temperature changes. The PV array is modeled using basic circuit equations. Its voltage current and power voltage characteristics are simulated with different conditions. It is noticed that output characteristics of PV array are affected by environmental conditions and conversion efficiency is low. This model can be used for build a photovoltaic circuit model for any photovoltaic array. All modules which form the photovoltaic system model are independently modeled and validated in Simulink.
Aspect and Rootstock Genotype Influence Leaf Stomatal Density in Macadamia sp. †

: We investigated the effects of three rootstocks (Beaumont, Daddow and WJMAS‐29), and two aspects (north and south), on leaf stomatal density (SD) of a common macadamia scion ‘HAES741’. Manual counting and artificial intelligence (AI) image processing methods were used to measure SD from the leaves of the scion grafted onto each rootstock. In both methods, rootstock and aspect showed significant effects on scion SD (352 stomata mm −2 in WJMAS‐29, 310 stomata mm −2 in Beaumont, 332 stomata mm −2 in Daddow; 358 stomata mm −2 in north and 305 stomata mm −2 in south). We discussed that variability in SD due to rootstock and aspect can be used to improve productivity of future orchards systems.
A Reinforcement Learning Approach for Smart Farming

At a basic level, the aim of machine learning is to develop solutions for real-life engineering problems and to enhance the performance of different computers tasks in order to obtain an algorithm that is highly independent of human intervention. The main lying ingredient for all of these, is, of course, data. Data is only valuable if it is transformed into knowledge, or, experience and the machine learning algorithm is only useful if it can make a prediction with high accuracy outside the examples in the training set. The field of machine learning intersects multiple domains such as data science, artificial intelligence, statistics, and computer science, but has appliances in any possible field that relies on decision making based on evidence, including healthcare, finance, manufacturing, education, marketing and recently, more and more in agriculture and farm-related management systems. As the Internet of Things and Cloud-Based solutions are introducing artificial intelligence in farming, the phenomenon of Big Data is going to impact the whole food-supply network. Machines that are connected with each other through a network or that are equipped with deep learning software or just with measurement systems are making the farming processes extremely data-driven. Fast decision-making capabilities might become a game-changing business model in this field.
A Comparative Evaluation of Deep Learning Approaches to Online Network Traffic Classification in Community Networks

Community networks are networks that are run by the citizens for the citizens. Communities build, operate and own open IP-based networks, which promotes individual and collective participation. These networks run with limited resources compared to traditional Internet Service Providers. Understanding how resources are used is necessary to ensure improved Quality of Service (QoS). The purpose of this paper is to determine whether deep learning can be used for traffic classification to help improve the QoS and traffic engineering in community networks. To do this, the deep learning architectures chosen were tested over a range of time and memory constraints, and they have been compared to a traditional machine learning model. After performing the experiments it was shown that deep learning is the best way to perform traffic classification in a low resource environment. The models provided prediction speeds fast enough to be used for real time classification, and they had a higher test set accuracy than the Support Vector Machine when measured over all memory constraints. The paper also shows that the Long Short-Term Memory architecture significantly outperformed the Multi-Layer Perceptron because it was able to learn the sequential aspects of the packet’s byte stream.
Research on Tourism Image Perception of Tang Paradise

In the Internet age, it is scientific to use the analysis of online texts to explore tourists' image perception of tourist attractions. This study selects Tang Paradise as a case site, uses ROST Content 6.0 software to analyze the web texts obtained from the Ctrip.com and Mafengwo website,obtains the tourism image of Tang Paradise from the perspective of tourists' perception. The results show: Tourists have more perceptions of tourist attractions in Tang Paradise, among which the perception of human resources is the deepest; semantic network analysis diagram, including "Tang Paradise - park - ticket" and other three important relationship chain;the overall perception of tourists is positive, but in terms of tourist consumption and tourism infrastructure, negative emotions account for a relatively high proportion . Based on the results of this analysis, relevant suggestions are made for the improvement of the tourist image of Tang Paradise.