Miracle-dz/UniFAR-FTUs huggingface dataset:
Extreme random forest method for machine fault classification

Recently, random forest (RF) as a highly flexible machine learning algorithm has been applied to medicine, biology, machine learning, computer vision and other fields, and has shown good application performance. Nevertheless, the operation efficiency and identification accuracy of RF algorithm are actually affected by the number of the decision trees. A novel RF model, referred to as the extreme random forest (ERF), was proposed to improve the ability of feature extraction and reduce the computation burden. In the ERF method, the dimensionality of the high-dimensional data is randomly reduced through the random mapping matrix, and the classification performance after dimensionality reduction is improved. In this way, the sample dimension of the input RF is greatly reduced, which improves the operation efficiency of the RF. Both theoretical analysis and experiment tests have verified the superiority of the proposed method. In the experimental part, the present ERF method was compared with other peer method in terms of diagnostic performance and computational efficiency. The comparison results showed that the ERF method has more advantages both in diagnostic accuracy and computational efficiency. In addition to mechanical fault diagnosis, the proposed ERF can also be used in other machine learning fields.
Molecular beam epitaxial growth of hexagonal boron nitride on Ni foils

Hexagonal boron nitride (h-BN) was synthesized by molecular beam epitaxy on polycrystalline Ni foils using borazine (B3N3H6) as precursor. Our photoemission analysis shows that several components of boron and nitrogen are detected, suggesting the complex nature of the bonds noticeably at the h-BN/Ni interface. The BN thickness was estimated by photoemission and the BN distribution by time-of-flight secondary ion mass spectroscopy. Due to the catalytic effect of the Ni substrate, this thickness is self-limited in the range 1–2 layers regardless of the borazine dose. A spatially resolved photoemission study was carried out before and after transfer of the h-BN on a Si substrate. It shows that a strong electronic coupling exists at the interface between h-BN and polycrystalline Ni, not only for (111) grains, which disappears after transfer on Si. In addition, we highlight the importance of detecting π plasmons in the photoemission spectra to confirm the hexagonal nature of BN.
3D-printed liquid metal-based stretchable conductors and pressure sensors

Microfluidic devices control fluids on the micrometer-scale and are commonly used for lab-on-chip applications, such as sensors, micropumps and biological analyzers. Commonly reported fabrication methods for achieving flexible microfluidic structures are labor-intensive, require many cumbersome steps, and have limited options for materials. This paper presents a rapid-manufacturing technique using a PolyJet 3D-printer for creating soft microfluidic substrates embedded with liquid metals to fabricate stretchable conductors and pressure sensors. By using this novel method, several spiral-shaped soft pressure sensors with multimaterial-based substrates are 3D-printed simultaneously in less than six minutes. Microfluidic channels with cross-sections ranging from 150 × 150 to 350 × 350 µm are successfully achieved in a soft substrate. This 3D-printing method allows fabrication of complex, enclosed channels without any photocurable support material, thus minimizing post-processing time. Simulation and experiments are conducted to characterize the quasi-static and dynamic properties of the fabricated pressure sensor. In particular, experimental results show that these 3D-printed microfluidic pressure sensors are robust, capable of withstanding high pressures up to 1 MPa.
Singular value penalization based adversarial domain adaptation for fault diagnosis of rolling bearings

Machinery fault diagnosis tasks have been well-addressed when sufficient labeled data of the tested machines are available. However, intelligent fault diagnosis methods trained with such labeled data generally fail in classifying unlabeled data due to data distribution discrepancy. To tackle this problem, a novel transfer learning method called singular value penalization adversarial network is proposed for fault diagnosis of rolling bearings, which first constructs a feature extractor to learn the shared feature representations between the source and target domains automatically, and then plays an adversarial training game between feature extractor and domain discriminator to reduce the domain shift and achieve domain adaptation. In particular, a new singular value penalization term is proposed and integrated into the domain adversarial network, which balances the distributions of largest singular values and boosts the discriminability of feature representations. The extensive transfer diagnosis experiments on two rolling bearing datasets validate the effectiveness and robustness of the proposed method, and the results show that our approach is superior to other methods under unlabeled data.
Optoelectronic oscillator for 5G wireless networks and beyond

With the development of 5G wireless network and beyond, the wireless carrier frequency will definitely reach millimeter-wave (mm-wave) and even terahertz (THz). As one of the key elements in wireless networks, the local oscillator (LO) needs to operate at mm-wave and THz band with lower phase noise, which becomes a major challenge for commercial LOs. In this article, we investigate the recent developments of the electronic integrated circuit (EIC) oscillator and the optoelectronic oscillator (OEO), and especially investigate the prospect of OEO serving as a qualified LO in the 5G wireless network and beyond. Both the EIC oscillators and OEOs are investigated, including their basic theories of operation, representative techniques and some milestones in applications. Then, we compare the performances between the EIC oscillators and the OEOs in terms of frequency accuracy, phase noise, power consumption and cost. After describing the specific requirements of LO based on the standard of 5G and 6G wireless communication systems, we introduce an injection-locked OEO architecture which can be implemented to distribute and synchronize LOs. The OEO has better phase noise performance at high frequency, which is greatly desired for LO in 5G wireless network and beyond. Besides, the OEO provides an easy and low-loss method to distribute and synchronize mm-wave and THz LOs. Thanks to photonic integrated circuit development, the power consumption and cost of OEO reduce gradually. It is foreseeable that the integrated OEO with lower cost may have a promising prospect in the 5G wireless network and beyond.
Research on the Path of Organizational Resources’ Utilization and Development of State-Owned Energy Enterprises in the New Era

Under the multiple-pressure of macroeconomic situation, self-reliance of science and technology, enterprise management reform, industrial transformation and upgrading, state-owned energy enterprises need to comprehensively examine the important value of organizational resources in the development of enterprise reform and transformation. Meanwhile, on the basis of grasping the external demands, expectations and key constraints faced by state-owned energy enterprises in the new era, it is critical to clarify the evolution direction of the organizational system of state-owned energy enterprises in the new era, and find the key path for state-owned energy enterprises to tap the potential of organizational resources and introduce high-quality organizational resources.
Review on electrochemical energy storage technology in power system and relevant materials

The coordinated development of energy storage technology and renewable energy is key to promote the green development in power system. Due to the cost reduction and superior performances of electrochemical energy storage technologies, more and more related demonstration projects have been constructed in recent years. The paper focuses on several electrochemical energy storage technologies, introduces their technical characteristics, application occasions and research progress of relevant materials in details. Finally, development trends of energy storage technology in the future are discussed and prospected based on the actual situations in the west of Inner Mongolia.
Most commonly used metallic biomaterials for plasma sprayed hydroxyapatite coatings

In load bearing implants metallic biomaterials have the first preference in orthopedic surgery because of their good mechanical properties which satisfied the prerequisite of human cortical bone. However metallic implants have limitations of poor wear resistance and release of metal ions resulting in to implant failure. To overcome these limitations hydroxyapatite based coatings on metal substrate can be used. The application of hydroxyapatite coating with the second reinforcement improve the fatigue strength of composite coatings. In this paper, commonly used metallic biomaterials for application of hydroxyapatite based composite coatings are discussed. Plasma spray coating technique with variable process parameters has been considered for this review. Presently plasma spray technique is commonly used for application of HA coatings in medical industry.
Effect of Die Design parameters on materials processed by Equal Channel Angular Pressing

Equal Channel Angular Pressing technique is used for grain refinement in bulk materials, where the material is passed through the die in which the two channels intersect at some angle, that result in finer grains. There are number of die design parameters which affects the production of ultra-fine grains. This paper presents the effect of die design parameters such as channel angle, corner angle, several passes and route followed for processing of the material for grain refinement. The results of different parameters are compared, and it was observed that the optimum values for producing maximum shear strain is for channel angle 90° and it reduces with the increase in channel angle. About 20° corner angles is found to suitable for filling the corner gap, around 4 to 6 passes, and route Bc leads to the ultrafine grained structure of homogeneous equiaxed grains separated by high angle grain boundaries in the materials. The sample of Al-TiO2 was prepared and its microstructure and mechanical properties were tested after equal channel angular pressing.
Performance Simulation of a PV Module with Shaded PV Cells

PV modules are very sensitive to shading. It is a well-documented fact that partial shading of a photovoltaic array reduces output power capability. The conventional single diode model for solar cell with series and shunt resistance is used for illustration. The effect of change in environmental condition like irradiance and temperature on output of photovoltaic module isstudied. The effect of shading on solar Photovoltaic (PV) model is evaluated by using a simulation model for simulating both the I-V and P-V characteristics curves for PV panels. The results are simulated by using the Matlab software. The potential of the simulation analysis is highlighted as a flexible and powerful tool for the design of new and more competitive PV module configurations for the collectors in solar panels.
New theoretical concepts for designing oxide interfaces with exoticproperties for electronics and spintronics

This thesis theoretically studies structural and electronic properties of perovskite manganese oxide superlattices by means of ab-initio calculations.Lanthanum manganese oxides, given with the generic formula La1−xAxMnO3 (LAMO) (A a divalent element), are an important class of perovskite manganese oxides due to their various exotic properties, such as giant and colossal magnetoresistance effect, rich phase diagrams with respect to doping, temperature or external fields, and intinsic large Curie temperature. These properties can be exploited in many potential technological applications such as spin valves or spin injectors. Controlling the properties of these materials can be done through deposition as thin films or as building blocks in superlattices. When x = 1/3, bulk La1−xAxMnO3 is ferromagnetic and metallic due to the double-exchange mechanism in the Mn 3d shell. When Mn is in a mixed valence state, the eg orbitals (dx2-y2 and dz2) are partially occupied, and can delocalize on neighboring Mn atoms only if the latter are ferromagnetically aligned. In very thin films, since the direction perpendicular to the substrate, c, is only a few unit cell thick, only in-plane (ab) interactions are important for the thermodynamic properties. By acting on the LAMO layer geometry, one can thus maximize the dx2-y2 occupancy and increase the magnetic exchange and related Curie temperature.Our aim was thus to design new materials with desired 3d orbital order so that to ensure desired magnetic properties.In this thesis, we worked on two types of superlattices. The first one was made of two undoped antiferromagnetic manganese oxides LaMnO3 and SrMnO3, i.e. [LaMnO3]n/[SrMnO3]m superlattices. We investigated the magnetic ground state for different n and m values in order to explain suprising experimental results. The second type of superlattices is composed of metallic LAMO layers with alternated insulating layers. Indeed, the superlattices with metal-insulator interfaces have a great potential in spin valves applications. Thus, we first considered the ferromagnetic-metallic/ferroelectric-insulating [LAMO]3/[BTiO3]3 superlattices (A= Sr or Ba, B=Ba or Pb) where the magnetic properties are reduced due to delocalization of dz2 electrons at the interface from Mn to Ti. In such superlattices, we clarified the role of the polarization of the ferroelectric layers and the role of the antiferrodistortive motions in the manganite layers. In order to prevent the delocalization taking place at the interface, we designed another superlattice with metallic-insulator interface where we replaced the insulator (BTiO3) with a simple oxide (BO); that is [LAMO]n/[BO]p superlattices (A= Sr or Ba, B=Ba, Sr or Mg and n=3 or 6, p=6 or 2). Within this new superlattice, we successully managed to promote dx2-y2 orbital occupancies at the interfaces which ensures a large magnetic moment at the interfaces and an expected large Curie temperature. We also showed the weak correlation between electrical conductivity and orbital ordering.
Effect of Online Service Quality Dimensions on Customer Satisfaction and Behavioral Intention: An Empirical Study

The research paper attempts to determine the online service quality dimensions that affect the customer satisfaction in online shopping and how it impacts the behavioral intention of the online consumers. This research work makes the use of ES-QUAL scale items to find out the effect that dimensions of online service quality have on customer satisfaction. E-S-QUAL (Parasuraman et al., 2005) was used as the theoretical framework of our study to find out the effect that each dimension of online service quality has on customer satisfaction and behavioral intention. The relationship between the e-service quality dimensions, overall online service quality and online customer satisfaction were formulated in the form of statements and hypothesis were developed to find out the relation between online service quality and online customer satisfaction and its impact on behavioral intention. Data from a survey of 60 online consumers was collected. Sampling method adopted for our research was non probability judgement sampling. The results confirm that there is a significant association between online satisfaction and the four dimensions of E-S-QUAL. Whereas Responsiveness and compensation were found to have no association with online customer satisfaction based on the data received from respondents. As found from the study that there was a strong positive association between customer satisfaction and behavioral intention. The paper makes a scholar contribution by examining the notion of e-service quality and how it relates with e-satisfaction while exploring unexamined consumers’ behavioral intentions.
Age at Diagnosis of Breast Cancer in Iran: A Systematic Review and Meta-Analysis

Background: Breast cancer is responsible for up to 25% of all cancers in Iran. The age at diagnosis of Iranian breast cancer patients starts a decade earlier than most of developed countries. This study aimed to evaluate the mean age at diagnosis of Iranian breast cancer patients. Methods: In this systematic review and meta-analysis, the mean age at diagnosis of Iranian breast cancer patients and its pattern between 2008 and 2017, were evaluated. All papers with age at diagnosis of histopathological verified breast cancer patients were considered eligible to enter to the analysis. We used databases including Medline/PubMed, Scopus, Embase, Cochrane Library, Iranmedex and SID for the search process. The meta-analysis was performed only on studies with separate data for female patients, using random-effects model, Mantel and Haenszel method and the Comprehensive Meta-analysis software. Results: Finally, 92 studies with 19,784 patients (both-genders) were included. The mean age at diagnosis had increased from 47.93 (2008) to 49.91 (2016) years. The meta-analysis was done on 78 studies containing of 15,071 female patients and the mean age at diagnosis was 46.76±1.19. There was a wide range of age at diagnosis within different provinces. The mean age at Hamadan and Khuzestan provinces were the lowest and highest, respectively (42.48±7.96 vs. 51.00±11.47). The heterogeneity of studies was statistically significant (I2=99.744). Conclusion: Mean age at diagnosis of Iranian women with breast cancer was 46.76±1.19. There was an increasing pattern in mean age of diagnosis at breast cancer patients within the past 10 years.
Labor Demand Response to Labor Supply Incentives: Lessons from the German Mini-Job Reform

IZA DP No. 14248 APRIL 2021 Labor Demand Response to Labor Supply Incentives: Lessons from the German Mini-Job Reform* This paper analyzes how firms respond to changes in tax benefits for low-earning workers and how such policies also affect high-earning workers. I explore establishment outcomes around Germany’s 2003 Mini-Job Reform, which expanded tax benefits for low-earning workers. I document that highly exposed establishments–high proportion of low-earning workers–increase their employees relative to non-exposed establishments–low proportion of such workers. This relative expansion is tilted towards high-earning workers, not targeted by the tax benefits. Nonexposed establishments substitute employment towards low-earning workers without expanding at the same pace. My findings are consistent with a model in which employment growth the policy intended is accompanied by a reallocation of employment and production between highly exposed firms and non-exposed firms, resulting in an efficiency loss. JEL Classification: H20, H24, H32, E24, E64, I38, J23, J38
An overview on bio battery unveiling potential

In the modern age there are so many power sources but one of the more efficient power sources in our Villages are the BioBattery, which is an alternate sources of energy. using wastewaterwhich is a major problem in rural India, Handy source of power generation. Further we can stored energy in the form of Carbohydrates, found in the waste biomass ,contains Microbial Fuel Cells. We can produce electricity in an MFC (Microbial Fuel Cells ) from domestic wastewater and at the same time accomplish biological wastewater treatment. So Bioreactors based on power generation in MFCs are a new approach to waste treatment and power generation.
Online Product Recommendation System using Sentiment analysis and Spam Filtering: A Review

: E-commerce has recently concentrated on the rise of internet retail platforms and can be recommended by multiple consumers who refer to product review opinions to pick their goods and products from their purchasing experience. But, if current product evaluation programs include customers' problems (eg. cost, power, structure, function, etc.) conventional recommendation systems do not recommend alternative products, it is also difficult to meet user requirements. In this paper, we suggest therefore a new product recommendation framework that analyses two forms of information: information on grievances and information on satisfaction from e-commerce review comments. Alternative things can be recommended to meet the needs and can resolve the product issue details as you browse. In this article, we would identify the extraction of complaint information by removing both negative information and positive information from product feedback and clarify alternative product recommendation approaches for complaints resolution and check the efficacy of complaint information extraction and alternative product recommendations.
Mark-Recapture Models for Estimation of Demographic Parameters

Population ecologists require robust estimates of survival and other demographic parameters for understanding the ecological and evolutionary drivers of wildlife population dynamics. Live encounter data from individual animals marked with unique tags or natural marking patterns are a key source of information for many species. Imperfect detection and losses to emigration can be challenging issues when tracking mobile organisms under natural conditions. Mark-recapture models utilize encounter histories for marked individuals where consecutive sampling occasions are coded with detection or nondetection data. Alternative models can then be fit as fixed-effect models with maximum likelihood methods in a frequentist framework, or as hierarchical models with random effects in a Bayesian framework. The Cormack–Jolly–Seber (CJS) model conditions upon first capture and uses forward-time modeling to estimate apparent survival corrected for the probability of encounter. More complex models extend the basic CJS model to estimate additional parameters. Time-since-marking models estimate apparent survival corrected for losses due to transients, age effects, and other factors. Temporal symmetry and Jolly–Seber models combine forwardand reverse-time modeling to estimate recruitment and population change without the need to parameterize a full matrix model. Robust design models adopt a nested sampling approach and are useful for investigating the dynamics of temporary emigration due to regional movements, dormancy, and intermittent breeding. Multistate models extend the singlestate CJS model to multiple categorical states and provide state-specific estimates of apparent survival and transition rates among sites, demographic classes, disease status, or other states. Extended multistate models allow for unobservable states or situations where state classifications may be uncertain. Other models combine live encounters from marked individuals with different types of auxiliary data. Mark-resighting models add counts of unmarked individuals to estimate total abundance. Joint models add data on dead recoveries or supplementary resightings to estimate true survival and site fidelity. Integrated population models combine live encounters with count and fecundity data to estimate immigration rates and population change. Mark-recapture models are powerful tools because they correct for imperfect detection and imperfect availability, they can control for transients, social structure, and other potential sources of heterogeneity, and they also allow joint analysis across independent datasets. Demographic parameters are estimated with less bias and greater precision, thereby providing a stronger foundation for addressing key questions in population biology, evolutionary ecology, and wildlife management.