Miracle-dz/UniFAR-FTUs huggingface dataset:
Rolling Bearing Fault Diagnosis Using Multi-Sensor Data Fusion Based on 1D-CNN Model

To satisfy the requirements of the end-to-end fault diagnosis of rolling bearings, a hybrid model, based on optimal SWD and 1D-CNN, with the layer of multi-sensor data fusion, is proposed in this paper. Firstly, the BAS optimal algorithm is adopted to obtain the optimal parameters of SWD. After that, the raw signals from different channels of sensors are segmented and preprocessed by the optimal SWD, whose name is BAS-SWD. By which, the sensitive OCs with higher values of spectrum kurtosis are extracted from the raw signals. Subsequently, the improved 1D-CNN model based on VGG-16 is constructed, and the decomposed signals from different channels are fed into the independent convolutional blocks in the model; then, the features extracted from the input signals are fused in the fusion layer. Finally, the fused features are processed by the fully connected layers, and the probability of classification is calculated by the cross-entropy loss function. The result of comparative experiments, based on different datasets, indicates that the proposed model is accurate, effective, and has a good generalization ability.
Comparison of Physical Activity Environments in Michigan Home-Based and Licensed Childcare Programs

ABSTRACT Introduction/Purpose Physical activity in young children is influenced by the childcare physical activity environment. Identifying differences between home-based programs and licensed centers can inform future interventions to facilitate physical activity and its benefits for all children. Our purpose was to compare the physical activity environment in home-based (n = 70) and licensed (n = 54) childcares. Methods Teachers/directors completed an electronic survey regarding respondent/program characteristics, the outdoor/indoor environment, and barriers to promoting physical activity. T-tests and Fisher’s exact tests compared outcomes by program type. Results Home-based programs had more overall (+1.5), active (+0.5), and attractive (+0.6) natural elements, and more portable or fixed (+1.9), creative fixed (+0.9), and screen time (+0.7) equipment compared with licensed centers, which were rated higher quality (+8.9 out of 50 points). Home-based programs provided more indoor time for physical activity (+2.1 min·h−1) and naptime (+3.1 min·h−1), similar outdoor and television time, longer bouts of indoor teacher-led activity (+6.1 min), and higher levels of activity while indoors (+0.5 on a scale from 1 to 7) compared with licensed centers. The most commonly reported barrier to promoting activity was cost of equipment (82.9%–87.8% of programs). Conclusions Despite being rated as lower quality by the state, home-based programs have many physical-activity-promoting attributes. Although some of our findings are in contrast to the extant literature, this may be due to the strong policies regarding home-based childcare programs in place in Michigan. Future research may aim to compare with other states and understand how these environmental differences impact physical activity participation.
Genetic diversity analysis of Glycyrrhiza uralensis using 8 novel polymorphic microsatellite markers

Licorice plant ( Glycyrrhiza spp.) is an important herb, but the major portion of the national demand is imported to Korea because the domestic production base is vulnerable. We performed basic molecular breeding research for domestic cultivation and production. All publicly available G. uralensis EST sequences, which totaled 56,089, were assembled into 4,821 unigenes and examined for microsatellites. Eight polymorphic microsatellite loci were identified and 16 G. uralensis and 6 G. glabra accessions , which were collected from different locations, were genotyped using the microsatellites. Genetic diversity within the accessions was estimated by construction of a dendrogram. The dendrogram was clustered into two groups. The results showed that there is a correlative genetic relationship between species. The microsatellite markers were found to be useful for diversity analysis as they are able to successfully distinguish the Glycyrrhiza
Systematics, biostratigraphy and paleoenvironmental investigation of early Ypresian Alveolina assemblages in the northern part of Isparta Angle (Keçiborlu, Isparta, SW Turkey) E-ISSN : 2651-3048 Bulletin of the Mineral

Thanetian-early Ypresian (middle Ilerdian) limestones from the northern part of Isparta Angle (Keçiborlu, Isparta, SW Turkey) contain rich benthic foraminiferal assemblage. Ilerdian beds of the Büyükkırtepe formation are characterized by high diversity of the following Alveolina species: Alveolina (Glomalveolina) cf. subtilis, A. A. (A.) varians, and A. (A.) vredenburgi . In this study, 30 different Alveolina species including two new species and a new subspecies namely as A. (A.) acari n. sp. , A. (A.) ozbahcensis n. sp. , and A. (A.) avsari fusunae n. ssp. were identified for the first time. Besides, some probable new subspecies that were unnamed yet due to the insufficient number of individuals were also defined and proposed. Despite having close stratigraphic distributions with coeval assemblages described in different regions of Tethyan Province, Alveolina assemblages of the study area exhibit some stratigraphical range differences and present SBZ 3-SBZ 8 biozone intervals. The obtained data show that the study area was a lagoon to low energy shallow marine paleoenvironment with normal salinity in Thanetian – middle Ilerdian interval.
Instachain: Breaking the Sharding Limits via Adjustable Quorums

—Sharding is a key approach to scaling the performance of on-chain transactions: the network is randomly partitioned into smaller groups of validator nodes, known as shards , each growing a disjoint ledger of transactions via state-machine replication (SMR) in parallel to other shards. As SMR protocols typically incur a quadratic message complexity in the network size, shards can process transactions signiﬁcantly faster than the entire network. On the downside, shards cannot be made arbitrarily small due to the exponentially-increasing probability that malicious nodes take over a sufﬁcient majority in small shards, compromising the security of SMR. In practice, this dictates relatively large shards with hundreds of nodes each, signiﬁcantly limiting the scalability beneﬁts of sharding. In this paper, we propose Instachain , a novel sharding approach that breaks the scalability limits of sharding by reducing the shard size to signiﬁcantly-smaller numbers than was previously considered possible. We achieve this by relaxing the liveness property for some of the shards while still preserving the safety property across all shards. To do this, we carefully adjust the quorum size parameter of the intra-shard SMR protocol to achieve maximum parallelism across all shards without compromising security. In addition, Instachain is the ﬁrst sharding protocol to adopt the stateless blockchain model in shards, which in conjunction with a novel cross-shard veriﬁcation technique allows the protocol to efﬁciently prevent double-spending attempts across signiﬁcantly-more shards than previous work.
Statistical anatomical modelling for efficient and personalised spine biomechanical models

Personalised medicine is redefining the present and future of healthcare by increasing treatment efficacy and predicting diseases before they actually manifest. This innovative approach takes into consideration patient’s unique genes, environment, and lifestyle. An essential component is physics-based simulations, which allows the outcome of a treatment or a disease to be replicated and visualised using a computer. The main requirement to perform this type of simulation is to build patient-specific models. These models require the extraction of realistic object geometries from images, as well as the detection of diseases or deformities to improve the estimation of the material properties of the studied object. The aim of this thesis was the design of a general framework for creating patient- specific models for biomechanical simulations using a framework based on statistical shape models. The proposed methodology was tested on the construction of spine models, including vertebrae and intervertebral discs (IVD). The proposed framework is divided into three well-defined components: The paramount and first step is the extraction of the organ or anatomical structure from medical images. In the case of the spine, IVDs and vertebrae were extracted from Magnetic Resonance images (MRI) and Computed Tomography (CT), respectively. The second step is the classification of objects according to different factors, for instance, bones by its type and grade of fracture or IVDs by its degree of degeneration. This process is essential to properly model material properties, which depends on the possible pathologies of the tissue. The last component of the framework is the creation of the patient-specific model itself by combining the information from previous steps. The behaviour of the developed algorithms was tested using different datasets of spine images from both computed tomography (CT) and Magnetic resonance (MR) images from different institutions, type of population and image resolution.
A Review on Multi-motor Synchronous Control Methods

Due to the requirements of industrial drive system for high output power, uniform torque distribution and accurate synchronous movement, the synchronous control methods of multi-motor system has drawn increasing attention. This paper refers to a large number of researches on synchronous control methods, and summarizes and compares different control structures and algorithms. Based on the evaluation criteria of tacking error, synchronization error and adjustment time, the advantages and disadvantages of three representative control algorithms, including proportional integral derivative (PID) control, model predictive control and sliding mode control, are studied through experiments. Finally, the development trend of multi-motor synchronous control is summarized and prospected.
Associations between Mental Resilience, Mood, Coping, Personality, and Hangover Severity

Extensive research exists on relationships between psychological constructs and alcohol consumption. However, research on relationships with hangover severity remains limited. This study aimed to assess the associations between mental resilience, mood (i.e., depression, anxiety, and stress), coping, personality, and hangover severity. A total of N = 690 participants completed an online survey by answering questions regarding their demographics, alcohol use, hangover prevalence and severity, and several psychological assessments (Brief Resilience Scale, DASS-21, Brief Cope, and Brief Version of the Big Five Personality Inventory). Significant associations were found between hangover severity and mental resilience, mood, and avoidant coping. Higher levels of mental resilience were associated with less severe hangovers, whereas poorer mood was associated with more severe hangovers. No significant associations were found with personality traits. These findings demonstrate that several associations between psychological constructs and hangover severity exist and suggest a role of psychological factors in the pathology of the alcohol hangover. As our findings contrast with the results of previous studies that did not report an association between mental resilience and the presence and severity of hangovers, further research is warranted.
Soil fungal and bacterial communities are altered by the incorporation of leaf litter containing a fungal endophyte

Litter decomposition plays a key role in nutrient cycling across ecosystems. The presence of Epichloë endophytes in grass plants affects litter decomposition. The overall effects of leaf litter containing Epichloë endophytes on the chemical and biological properties in non‐rhizosphere soils have not previously been examined. The current study is aimed to understand the effect of direct incorporation of leaf litter from Epichloë endophyte‐infected perennial ryegrass (Lolium perenne) on soil chemical characteristics, and fungal and bacterial biodiversity. Firstly, fresh leaf litter of the endophyte Epichloë festucae var. lolii‐infected (E+) and endophyte‐free (E−) L. perenne were incorporated into the soil, and then samples were collected from E+ and E− litter incorporated soil at T0, T1, T2 and T3 (0, 120, 240 and 360 days) for chemical and sequencing analyses. The Epichloë‐containing leaf litter incorporation changed the soil microbial environment by enhancing the soil organic carbon (SOC), total nitrogen (TN), total phosphorus, NH4+–N and NO3−–N contents, and acidifying soil pH. The endophyte had stronger effects on soil bacteria than soil fungi when the litter was determined with and without the endophyte. Litter containing the Epichloë endophyte significantly increased the absolute abundance of the 16S rRNA gene and relative abundances of the Actinobacteria, Nitrospirae and Gemmatimonadetes, while significantly decreasing the relative abundances of the Planctomycetes and Rokubacteria and the diversity in soil bacteria community. There was no significant effect of endophyte‐containing leaf litter incorporation on the absolute abundance and diversity of the soil fungal community except the increment in the relative abundance of Rozellomycota. Soil pH and the SOC‐to‐TN ratio (C:N) were the main factors influencing the soil bacterial community, and the presence of E. festucae var. lolii was directly and positively related to the soil bacterial diversity. The current study established that Epichloë endophyte‐infection altered the abundance and diversity of the soil bacterial community by affecting leaf litter quality and increasing soil chemical properties after litter incorporation.
Effects of Forest Healing Anti-Aging Program on Psychological, Physiological, and Physical Health of Older People with Mild Cognitive Impairment

This study aimed to determine the effect of a forest healing anti-aging program on psychological, physiological, and physical health in older people with mild cognitive impairment (MCI). Twenty-two older people with MCI living in the city participated in a forest healing anti-aging program. Psychological indicators included the mini-mental state examination (MMSE), Beck depression inventory (BDI), profile of mood states (POMS), World Health Organization Quality of Life instrument (WHOQOL), and the Pittsburgh sleep quality index (PSQI). Physiological indicators included vital signs, body composition, and blood analysis. Physical indicators included the senior fitness test (SFT), muscle strength, spatiotemporal parameter of gait, static balance, and dynamic balance. Psychological, physiological, and physical indicators were evaluated at first and second pre-measurement, post-measurement, and one-month follow-up. MMSE, BDI, POMS, WHOQOL, body composition, blood analysis, SFT, muscle strength, spatiotemporal parameter of gait, and dynamic balance were significantly different between pre- and post-measurement. Beck depression inventory, POMS, WHOQOL, PSQI, SFT, muscle strength (elbow flexor muscle, knee extensor muscle), spatiotemporal parameter of gait significantly improved continually until the one-month follow-up. In conclusion, the forest healing program had a positive effect on the psychological, physiological, and physical health of older people with MCI.
Ferramenta PPCensor: detecção de pornografia em tempo real no streaming de vídeo

Este artigo apresenta a ferramenta Private Parts Censor (PPCensor) para detecção de objetos de natureza pornográfica implementado como um proxy. Para tanto, a ferramenta efetua a análise em tempo real de maneira transparente dos frames de vídeos que estão sendo visualizados por usuários. Para a detecção dos objetos pornográficos, um detector de objetos é previamente treinado com a PPO (Private Parts Object Dataset). Quando PPCensor identifica um frame contendo partes íntimas (objetos), o conteúdo é ocultado do vídeo em exibição sem a necessidade de iteração ou a exigência de processamento no dispositivo do usuário. Os resultados da avaliação mostram que PPCensor é capaz de detectar partes íntimas em tempo real durante transmissões de vídeo.
Bidirectional Isolated Dual-Active-Bridge (DAB) DC-DC Converters Using 1.2-kV 400-A SiC-MOSFET Dual Modules

This paper describes the 750-Vdc, 100-kW, 20kHz bidirectional isolated dual-active-bridge (DAB) dcdc converters using four 1.2-kV 400-A SiC-MOSFET dual modules with or without Schottky barrier diodes (SBDs). When no SBD is integrated into each dual module, the conversion efficiency from the dc-input to the dc-output terminals is accurately measured to be 98.0% at the rated-power (100 kW) operation, and the maximum conversion efficiency is as high as 98.8% at 41-kW operation, excluding the gatedrive and control-circuit losses from the total power loss. The bidirectional isolated DAB dc-dc converters are so flexible that series and/or parallel connections of their individual input and output terminals make it easy to expand the voltage and current ratings for various applications such as the so-called “solid-state transformer” or “power electronic transformer. ”
How do cities challenge patterns of demand? Characterising the local governance of climate change in Nordic cities

Meeting international climate targets will require deep and rapid shifts in urban demand patterns. While the literature has emphasized the role played by cities in the response to climate change, it remains unclear whether or how urban-level interventions actually affect possibilities for low-carbon living, and contribute to the re-configuration of everyday practices. In this paper, we use a social practice lens to understand how, and to what extent a range of Nordic cities target everyday demand patterns in the development of low-carbon policies. Contemporary demand-side approaches have been critiqued for their focus on the provision of low-carbon technologies and individual-level interventions. Instead, we argue that understanding how measures target and intervene in everyday practices provide a relevant lens for approaching the success of low-carbon interventions. Using an intervention-in practice-framework to understand urban interventions, we find that current measures rely heavily on non-committal measures in the domains of mobility and housing and forms of household self-governance. This paper concludes by discussing the policy implications of taking a practice view in developing climate interventions in urban setting, arguing that such perspective broadens the range of governance approaches adopted by cities to govern a reduction of urban emissions.
Digital Mapping Algorithms to Estimate Soil Salinity in Indira Gandhi Nahar Pariyojana (IGNP) Command area of India

In the present study, the distribution of salinity was investigated using digital soil mapping (DSM) algorithmsin 5 km buffer zone of both side of Indira Gandhi Nahar Pariyojana (IGNP) canal system of Suratgarh tehshil in Rajasthan. To achieve this goal, 64 soil samples were used with 21 environmental covariates and 3 DSM algorithms. Result from the study showed that the difference between the minimum and maximum ECe is very high (35.55 dS m-1) in the different irrigation zone of IGNP canal system. The ECe ranged from 0.50 to 36.05 dSm-1. Results indicated that the most important environmental covariates were annual precipitation, elevation and valley depth. Among the DSM algorithms, RF model showed the best performance in predicting ECe at the regional level. Results showed that the RF algorithm could predict ECe with an R2, RMSE and MAE of 0.701, 3.367 and 1.722, respectively. RF and QRF showed similar performance in predicting ECe, while SVM showed lower efficiency than the other models in terms of R2 and prediction errors. Salinity prediction map shows that the vulnerability to soil salinity is high in Anupgarh branch of canal, and low in the IGNP main and Bikaner canal area. Furthermore, the model developed in this study provides comprehensive guidance for the land planners and decision makers to develop amicable strategies for management of IGNP canal system.
Histopathological Features Of Denosumab Treated Giant Cell Tumours Of Bone "A Single Institutional Experience" At A Tertiary Care Center, Karachi.

BACKGROUND Giant cell tumour (GCT) is a primary benign, locally aggressive bone tumour. Treatment is surgical however, denosumab has been increasingly used as a treatment in recurrent or unresectable locally advanced GCT because of its effect in reducing tumour size. Denosumab treated GCT can exhibit a wide array of histopathological features resulting in diagnostic problems for pathologists. Our study aimed at identifying these histopathological features to aid pathologists in reaching a correct diagnosis. METHODS Our study included 20 patients of biopsy-proven GCT cases treated with denosumab. We received specimens for histopathological examination in our institution from January 2018 to March 2020. The demographic and clinical data of these patients were retrieved from the Health Management Information System (HMIS). The slides were retrieved and studied for histopathological changes. RESULTS The mean age of patients in our study was 29.5 years. There were 11 males and 9 females. Distal radius was most commonly involved bone. On histopathological examination, ovoid to spindle mononuclear stromal cells were seen. Total absence of osteoclast like giant cells was seen in 10 (50%) cases, whereas 3 (15%) cases showed a marked reduction in osteoclast like giant cells. CONCLUSIONS Denosumab treated GCT of bone can exhibit a wide spectrum of histopathological features. Pathologists need to be mindful of these features. Correlation of histopathological findings with clinical history and radiological features is important to prevent erroneous diagnosis. Treatment history of patients with denosumab is essential as incorrect diagnosis can be made if the history of denosumab treatment is not provided.
Chemical investigation, quality assessment, and antimicrobial activity of davana (Artemisia pallens Wall. ex DC) essential oil collected from different locations in India

ABSTRACT Artemisia pallens Wall. ex DC, commonly known as davana, is cultivated in India for extraction of its essential oil (DO). In this study, DO collected from thirteen locations (DO1-DO13) and those extracted from six different phenophases and different plant parts were investigated using GC-FID and GC-MS. Altogether, 84 constituents were identified, forming 81.0–96.2% of the total oil composition. Major components of the oils were cis-davanone (17.4–65.1%), bicyclogermacrene (4.0–22.0%), cis-methyl jasmonate (0.4–8.5%), β-eudesmol (0.3–6.6%), davana ether isomer (0.5–6.1%), trans-ethyl cinnamate (1.4–6.1%), and germacrene D (0.1–4.7%). Among all tested oils, the DO10, having low cis-davanone content (27.5%), was found more potent against test microorganisms. The oils collected from different locations showed variations in their physical properties, chemical composition, and antimicrobial activity. Based on the yield and cis-davanone content, the flower bud and full-flowering stages could be suitable for harvesting good quality oil in north Indian plains.