Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-frequency Weak Signal Detection Based on EMD After De-noising by Adaptive Re-scaling Frequency-shifted Band-pass Stochastic Resonance

Aiming at the detection problem of the multi-frequency signal under noise background,a novel method based on empirical mode decomposition(EMD) after de-noising by adaptive re-scaling frequency-shifted band-pass stochastic resonance is proposed.In this method,different frequency bands of the signal are processed by re-scaling sub-sampling compression to make each frequency band meet the conditions of stochastic resonance.Further parameters are adaptively optimized according to noise intensity and the weak signal frequency components are enhanced through stochastic resonance system.Before the enhanced components of the signal are synthesized,they are processed through band-pass filter only leaving the enhanced sections of the signal,to achieve the enhancement signal.The processed signal is decomposed by EMD into intrinsic mode functions to achieve detection of multi-frequency weak signals.The simulation results show that the proposed method,can enhance the signal amplitude,reduce the false component and improve the accuracy of the EMD algorithm,effectively detect multi-frequency weak signal submerged by noise.
The hydrological and environmental aspect of low flow assessment in ungauged basins - a case study in the Juzna Morava river basin

Eighteen low flow indicators are considered in the research of sixteen hydrological stations in the Juzna Morava river basin. The indicators are estimated by statistical analysis and grouped as hydrological and environmental indicators. A crosscorrelation between all indicators is assessed. Environmental flows at hydrologic stations are obtained by the GEP method. The environmental low flow indicators are transferred to two small ungauged basins by regression with physiographic characteristics. The adjustment of environmental flows at ungauged basins is performed according to locations of the donor stations in the hydrogeological regions of the studied area.
Semi-integral Bridge Scour Prevention by Using 'Epipremnum aureum'

Integral bridges are jointless bridges which perform well in service and give long-term benefits. They are cheap to construct and require less maintenance compared to conventional bridges with expansion joints. Preservation and prevention of integral bridge scour at bridge foundation are the critical issues to be solved by hydraulic engineers. Monitoring and control of local scour at semiintegral bridge piers and combined piles are very crucial since the position is in the main channel. The aim of this study is to develop an unconventional preservation for reducing the scour at integral bridge for two uniform sand beds. Epipremnum aureum was chosen as an environmental scour protection in this study since it is environmental friendly, practical and very economical. Experimental works involved different flow rates for sand sizes of d50 = 0.8 mm, d50 = 0.26 mm and d50 = 0.13 mm were conducted in Hydraulics Laboratory of University Malaya, Kuala Lumpur, Malaysia. This research contributed a new method in managing scour at integral bridge by using a specific plant that could preserve the nature. Epipremnum aureum was proven could be applied as an unconventional protection for minimizing the effects of scour at integral bridge in the future.
Sizing Renewable Generation and Energy Storage in Stand-Alone Microgrids Considering Distributionally Robust Shortfall Risk

Renewable generation has grown rapidly these years due to its advantages in low environmental impacts. Stand-alone microgrid with renewable generation and energy storage is a promising option in remote areas beyond the reach of an existing power grid. This paper proposes a multiobjective optimization model to co-optimize the sizes of renewable generation and energy storage in stand-alone microgrids, which minimizes the load shedding risk and the total investment cost. The load shedding degree is obtained by an optimal operation problem and measured by shortfall risk, considering the uncertainties of demand and renewable resources. To deal with the inaccurate empirical distribution, distributionally robust shortfall risk is further established under a Wasserstein-metric-based ambiguity set, and an equivalent distributionally robust formulation is obtained. Then a conservative approximation is developed, and the resulting problem appears to be a bi-objective linear program. The Pareto frontier is proven to be piecewise linear, and the analytical expression of the Pareto frontier is derived. Case studies demonstrate the effectiveness and performance of the proposed method.
Breadwinning, migration, and nation-building: a critical scoping review of men, masculinities, and social change in post-Soviet Uzbekistan

ABSTRACT Uzbekistan, a former Soviet republic, is currently experiencing dramatic social changes as a result of both Western and Eastern influences. Notions of masculinity and what it means to be a man continue to change for Uzbek men. However, research theorizing gender and social change in Uzbekistan tends to focus on women, and as a result we know very little about the historical and contemporary identities, experiences, and subjectivities of men in Uzbekistan. The aim of this scoping review is to provide an overview of Uzbek masculinities and systematically examine how Uzbek masculinities have been studied locally and internationally in order to further enhance our understanding of post-Soviet transitions. This review identified 27 research publications in English and Russian between 1991 and 2020 focusing on Uzbek masculinities. Drawing from a wide range of disciplines, the review finds that overall, research has sought to make connections between two ideas: Uzbek masculinities and men's responsibilities in relation to breadwinning and labor migration, and the role of the nation-state in shaping a gendered nationalism as a result of post-colonial influences. The article concludes by highlighting the underrepresentation of neo-coloniality's role in shaping research culture in Uzbekistan and influencing our understanding of post-Soviet transitions.
Is It Time to Test the Antiseizure Potential of Palmitoylethanolamide in Human Studies? A Systematic Review of Preclinical Evidence

Antiseizure medications are the cornerstone pharmacotherapy for epilepsy. They are not devoid of side effects. In search for better-tolerated antiseizure agents, cannabinoid compounds and other N-acylethanolamines not directly binding cannabinoid receptors have drawn significant attention. Among these, palmitoylethanolamide (PEA) has shown neuroprotective, anti-inflammatory, and analgesic properties. All studies examining PEA’s role in epilepsy and acute seizures were systematically reviewed. Preclinical studies indicated a systematically reduced PEA tone accompanied by alterations of endocannabinoid levels. PEA supplementation reduced seizure frequency and severity in animal models of epilepsy and acute seizures, in some cases, similarly to available antiseizure medications but with a better safety profile. The peripheral-brain immune system seemed to be more effectively modulated by subchronic pretreatment with PEA, with positive consequences in terms of better responding to subsequent epileptogenic insults. PEA treatment restored the endocannabinoid level changes that occur in a seizure episode, with potential preventive implications in terms of neural damage. Neurobiological mechanisms for PEA antiseizure effect seemed to include the activation of the endocannabinoid system and the modulation of neuroinflammation and excitotoxicity. Although no human study was identified, there is ground for testing the antiseizure potential of PEA and its safety profile in human studies of epilepsy.
Galactic Air Improves Ancillary Revenues with Dynamic Personalized Pricing

Ancillaries are a rapidly growing source of revenue for airlines, yet their prices are currently statically determined using rules of thumb and are matched only to the average customer or to customer groups. Offering ancillaries at dynamic and personalized prices based on flight characteristics and customer needs could greatly improve airline revenue and customer satisfaction. Through a start-up (Deepair) that builds and deploys novel machine learning techniques to introduce such dynamically priced ancillaries to airlines, we partnered with a major European airline, Galactic Air (pseudonym), to build models and algorithms for improved pricing. These algorithms recommend dynamic personalized ancillary prices for a stream of features (called context) relating to each shopping session. Our recommended prices are restricted to be lower than the human-curated prices for each customer group. We designed and compared multiple machine learning models and deployed the best-performing ones live on the airline’s booking system in an online A/B testing framework. Over a six-month live implementation period, our dynamic pricing system increased the ancillary revenue per offer by 25% and conversion rate by 15% compared with the industry standard of human-curated rule-based prices.
Recent Research on and Prospects regarding Disaster Prevention Technology

Various natural disasters have occurred in Japan due to geological and meteorological conditions, causing significant human loss and economic damage. Disaster prevention technology for railways has been developed through experience and has contributed to mitigating damage. Since the 2011 off the Pacific coast of Tohoku Earthquake, however, the paradigm of disaster prevention has shifted. Japanese Government disaster prevention now focuses on mitigating the impact of and resilience against large-scale disasters caused by forces larger than those considered up until now. This paper introduces the results of recent research into disaster prevention technology, and describes research plans for mitigating the impact of and resilience against large-scale disasters.
Performance improvement of rectifiers for WPT exploiting thermal energy harvesting

This paper proposes a combined harvesting system to improve the efficiency and flexibility of autonomous wireless network nodes, supplied by means of wireless power transfer technique. In particular, a mixed system for electromagnetic (EM) and thermal Energy Harvesting (EH), conceived for passive nodes of wireless sensor networks and radio frequency identification tags, is described. The proposed system aims at increasing the effectiveness and the efficiency of the EH system by integrating an antenna and a rectifier with a Thermo-Electric Generator (TEG) able to perform thermal EH. The energy provided by the thermal harvester is exploited twice: to increase the rectifier efficiency by providing a voltage usable to improve the bias condition of the rectifying diode, and to provide additional dc energy, harvested for free. Ultimately, a great efficiency improvement, especially at low incident RF power, has been observed. The design methodology and the EM performance of a quarter-wavelength patch antenna, integrated with the TEG are resumed. Then, a test campaign to evaluate the thermal EH performance has been carried out. Afterward, a rectifier with variable bias voltage, operating at the same frequency of the antenna, has been opportunely designed to exploit the harvested thermal energy to bias the diode. A measurement campaign has been then carried out to test the efficiency increment obtained and to validate the proposed solution.
Directional and fluctuating asymmetries in Cavall Pirinenc Català breed molars

Deviations from expected perfect symmetry in biological forms can occur, and organisms develop several kinds of asymmetries. Among others, there are fluctuating asymmetry (FA) and directional asymmetry (DA). Thirty-two complete skulls were obtained from horses belonging to the"Cavall Pirinenc Catala" breed and the mesiodistal and the palatinovestibular lengths of the right and left upper molar series were analyzed in order to study FA and DA. Neither FA nor DA were detected in the studied sample. The results of this study will provide researchers with new morphological information about natural teeth wearing (based on grazing) and may also be used as a reference for designing experimental studies, especially on mandibular catch-up growth, and as an aid to zooarchaeologists in evaluating results from buried animal studies for comparison with living equine populations.
Meeting the Needs of Students With Emotional and Behavioral Disorders During the COVID-19 School Closures

The COVID-19 global pandemic left many educators making an emergency transition to remote instruction when schools were initially closed. Although this transition was likely difficult for most students, it may have been particularly difficult for students with emotional or behavioral disorders, who have complex and resource-intensive social, emotional, and behavioral needs. The purpose of this study was to examine the extent to which special educators and related service providers felt they were able to meet those needs in the context of the pandemic occurring in the Spring of 2020. Results indicated respondents’ perceptions of their ability to meet students’ needs and implement their students’ Individualized Education Programs (IEPs) were moderated by policies on remote instruction and students’ access to technology. In addition, respondents suggested district- and school-level response strategies, professional development on remote instruction, access to the internet at home, and additional technology would be helpful in future school closures. Implications and limitations are discussed.
Hardware-Aware 
In Situ
 Learning Based on Stochastic Magnetic Tunnel Junctions

One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities of nanosecond operation and compatibility with existing microelectronics. Considering large-scale, viable neuromorphic systems however, variability of device properties is a serious concern. In this paper, we show an autonomously operating circuit that performs hardware-aware machine learning utilizing probabilistic neurons built with stochastic magnetic tunnel junctions. We show that $in \ situ$ learning of weights and biases in a Boltzmann machine can counter device-to-device variations and learn the probability distribution of meaningful operations such as a full adder. This scalable autonomously operating learning circuit using spintronics-based neurons could be especially of interest for standalone artificial-intelligence devices capable of fast and efficient learning at the edge.
Data Transmission with Vestigial-Sideband-4-Phase-Shift-Keying (VSB-4-PSK)

Vestigia] sideband transmission in 4-PSK systems will in general cause crosstalk between the two channels with orthogonal carriers. The absolute value of this crosstalk is the same as in double sideband partial response transmission and therefore the same decoding methods can be used with the same results. By using a preand postequalization technique, however, some additional data transmission capacity depending on the width of the vestigial sideband can be achieved. This method is described and experimental results are given. Übersicht: Restseitenbandübcrtragung in 4-PSK-Systemen verursacht normalerweise Übersprechen zwischen den beiden Kanälen mit orthogonalen Trägern. Betragsmäßig ist dieses Übersprechen gleich dem bei Zweiseitenband-Partial-Response-Übertragung. Deshalb können auch dieselben Decodiermethoden mit den gleichen Ergebnissen verwendet werden. Durch eine Vorund Nachentzerrungstechnik läßt sich jedoch etwas zusätzliche Datenübertragungskapazität abhängig von der Bandbreite des Restseitenbandes erzielen. Diese Methode wird beschrieben, und experimentelle Ergebnisse werden angegeben. Für die Dokumentat ion: Vierphasenumtastung / Restseitenbandübertragung / Kompensation des Übersprechens / Vorund Nachentzerrung
Privacy-Preserving Threshold-Based Image Retrieval in Cloud-Assisted Internet of Things

Encrypted image retrieval is a promising technique for achieving data confidentiality and searchability the in cloud-assisted Internet of Things (IoT) environment. However, most of the existing top-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> ranked image retrieval solutions have low retrieval efficiency and may leak the values and orders of similarity scores to the cloud server. Hence, if a malicious server learns user background information through some improper means, then the malicious server can potentially infer user preferences and guess the most similar image content according to similarity scores. To solve the above challenges, we propose a privacy-preserving threshold-based image retrieval scheme using the convolutional neural network (CNN) model and a secure <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-nearest neighbor (kNN) algorithm, which improves the retrieval efficiency and prevents the cloud server from learning the values and orders of similarity scores. Formal security analysis shows that our proposed scheme can resist both ciphertext-only attack (COA) and chosen-plaintext attack (CPA), and extensive experiments demonstrate that our proposed scheme is efficient and feasible for real-world data sets.
Competitiveness framework to support regional-level decision-making in the wine industry: a systematic literature review

This study aims to identify the main performance indicators and group them in dimensions within a regional competitiveness framework to support decision-making in the wine industry. For this research, a systematic literature review (SLR) was conducted in the Scopus database. There is a limited number of studies identifying indicators with impact on the performance of wine regions, and even fewer studies including indicators in an integrated approach to measure the different dimensions of wine regions’ performance. From a set of 85 papers, only 9 studies related to performance indicators with a specific focus on the regional level were considered. We document that under a convention framework, economic and territorial indicators cover 84.90% of all SLR indicators analysed, and under a regional competitiveness framework, infrastructure and innovation and intellectual capital indicators fill 81.25% of all the indicators. As this group of indicators is limited to a set of sub-dimensions, we found that several groups of indicators are misrepresented, such as the ones related to human and socio-cultural capital areas, which play a crucial role in the regional competitiveness of the wine industry. This paper contributes to the literature identifying indicators according to convention and regional competitiveness frameworks in three dimensions – economic, environmental and territorial dimensions and five main areas – productive capital, human capital, socio-cultural capital, infrastructure and intellectual capital. These indicators are to be used at regional-level to support decision-making in the wine industry. For regional entities, it discloses the most pertinent indicators which need improvement to craft regional strategies. This framework is of added value for policymakers to customize their support programmes so that specific producers can enhance their competitive strategies. It could also be deployed in teaching programmes as a tool to address the importance of aligning different types of indicators to achieve better performance in the wine industry.
Twitter Engagement in Media Organizations: The Case of the Greek National Broadcasting Corporation

A key parameter in the strategy of news organizations remains the exploitation of factors (such as post time and post type) that enhance the engagement level within online communities on social media. The purpose of this paper is to examine the relationship between post time and post type in correlation with audience response in the Twitter digital platform. Specifically, the study aims to ascertain how the two specific variables affect user engagement with its Twitter posts and how they shape the effectiveness of communication on social networks. The analysis includes 7.122 tweets of the Greek National Broadcasting Corporation (ERT) over four months. Moreover, the study analyzes the tone of user comments on the Twitter posts of the specific public media organizations to understand in-depth how the users communicate their views publicly. The collection of comments lasted seven weeks and they numbered 265 in 2639 tweets. Regarding the post time variable, the study came to important findings on user behavior during the 24 h, as the number of Retweets appears to increase in the morning compared to the afternoon. It was also found that as time goes on, the user is interested in leaving his personal opinion. Regarding the correlation of post type with user engagement, it was found that the accompaniment of a tweet with audiovisual material has a tempting effect on users.
Increased synovial galectin-3 induce inflammatory fibroblast activation and osteoclastogenesis in patients with rheumatoid arthritis

Objective Galectin-3 (Gal-3) has been suggested as a proinflammatory mediator in rheumatoid arthritis (RA). We aimed to study clinical and pathogenic aspects of Gal-3 in RA. Method Plasma samples from healthy controls (n = 48) and patients with newly diagnosed, early RA were assayed for soluble Gal-3. In patients with chronic RA (n = 18), Gal-3 was measured in both plasma and synovial fluid. Synovial fluid mononuclear cells were used to purify fibroblast-like synoviocytes (FLSs) and osteoclasts. Monocultures of FLSs and autologous co-cultures of FLSs and peripheral blood mononuclear cells were established and co-incubated with a Gal-3 inhibitor. Results Patients with early and chronic RA had persistently increased plasma levels of Gal-3 compared with controls. However, changes in plasma Gal-3 at the level of individuals were associated with long-term disease activity. In seropositive early RA patients, all patients with decreasing plasma Gal-3 from 0 to 3 months had low disease activity after 2 years (p < 0.05). Gal-3 levels in synovial fluid were markedly elevated. In vitro, co-incubation with a Gal-3 inhibitor (GB1107, 10 µM) led to a significant reduction in both interleukin-1β and tumour necrosis factor-α secretion from FLS monocultures (both p < 0.05) and decreased monocyte-derived osteoclastogenesis compared with controls (both p < 0.05). Conclusions Our findings underscore the role of Gal-3 regarding disease activity and tissue destruction in RA. An initial decrease in plasma Gal-3 levels predicted decreased long-term disease activity. Correspondingly, a Gal-3 inhibitor decreased the activity of inflammatory FLSs and osteoclastogenesis in patients with RA.