Miracle-dz/UniFAR-FTUs huggingface dataset:
A simple and scalable approach to hollow silicon nanotube (h-SiNT) anode architectures of superior electrochemical stability and reversible capacity

Strain engineered unique architectures of silicon nanotubes have garnered tremendous attention as high capacity and stable lithium-ion battery (LIB) anodes. However, the expensive nature of the hitherto synthesis techniques used to produce the silicon nanotubes combined with the inferior yield and poor loading densities have rendered these unique morphologies unattractive for commercial LIB systems. In this study, we report for the first time, a simple, facile, and more importantly, recyclable sacrificial template based approach involving magnesium oxide (MgO) nanorods for producing scalable quantities of hollow silicon nanotubes (h-SiNTs) architectures. Electrodes fabricated from these h-SiNTs derived from this novel scalable approach exhibit equitable loadings and reversible capacities in excess of 1000 mA h g−1 at a high current density of 2 A g−1 for nearly 400 cycles, combined with a very low fade rate of only 0.067% loss per cycle. The high capacity, good current rate characteristics combined with excellent charge-transfer kinetics as well as the long cycle life of these engineered h-SiNTs render this approach viable for industry scale while also boding promise for practical applications.
HIGH-INVOLVEMENT WORK SYSTEMS AND TRAINING OPPORTUNITIES FOR YOUNGER HIGHLY EDUCATED EMPLOYEES

This paper explores the relationship between the training policy of the firm and the nature of the work system adopted at the establishment level. The literature has shown that high-involvement work systems are associated with more inclusive and more effective training. Based on a representative sample of establishments in EU countries, this paper shows that when work systems are more participative training programmes display a higher probability of focusing on future rather than current skill requirements. In addition, the work system adopted significantly moderates the probability of accessing specific types of training by younger educated employees.
Mark Gillings, Piraye Hacıgüzeller and Gary Lock. Re-Mapping Archaeology: Critical Perspectives, Alternative Mappings (London: Routledge, 2020, 324pp., 76 figs, hbk, ISBN 978-1-138-57713-8, eBook ISBN 978-1-351-26772-4)

pubblicazioni Eisenberg, J.M. 1992. The Aesthetics of the Forger: Stylistic Criteria in Ancient Art Forgery. Minerva, 3(3): 10–15. Faude-Nagel, C. 2013. Kunstfälschung & Provenienzforschung am Beispiel von drei Fälschungen aus dem aktuellen Kunstmarkt. Mainz: Chorus. Frieman, C. 2010. Imitation, Identity and, Communication: The Presence and Problems of Skeuomorphs in the Metal Ages. In: Eriksen, B.V. , ed. Lithic Technology in Metal Using Societies. Højbjerg: Jutland Archaeological Society, pp. 33–44. Grafton, A. 1990. Forgers and Critics: Creativity and Duplicity in Western Scholarship. London: Collins & Brown. Jones, M. 1990. Introduction. In: Jones, M. , Craddock, P. T. , Barker, N. & British Museum, eds. Fake? The Art of Deception. London: British Museum Publications, pp. 11–22. Jones, M. ; Craddock, P.T. , Barker, N. & British Museum, eds. 1990. Fake? The Art of Deception. London: British Museum Publications. Lessing, A. 1965. What is wrong with a forgery? The Journal of Aesthetics and Art Criticism, 23(4): 461–71. Neuchâtel, S. & Kaeser, M. 2011. L’Âge du faux : L’authenticité en archéologie. Hauterive: Laténium. Nagel, A. 2004. The Copy and Its Evil Twin: Thirteen Notes on Forgery. Brooklyn, NY: Immaterial Inc.
Classifying Facial Expression using Convolution Neural Network

The human-computer interaction system is a success by deriving an effective facial expression recognition function. But it remains a difficult activity to understand facial speech. This paper sets out a novel Recognition of facial expression approach to the task. The approach proposed is motivated by the performance of the Convolutional Neural Networks (CNN) on the face trouble with identification. Unlike other plays, we focus on having good accuracy while requiring only a small sample data for training. The proposed approach is tested on Japanese Female Facial Expression (JAFFE). The accuracy increased compared with state-of-art results on the JAFEE dataset, where it achieved 95%.
Measuring urban and rural establishment innovation in the United States

ABSTRACT What are the best proxies for innovation and do the best proxies vary by type of region? A commonly used and easily obtained measure is patenting, but there may be disadvantages to using it exclusively. We compare patents to 39 alternative innovation measures in terms of how they perform across tradeable urban and rural establishments. Data are from the USDA’s 2014 National Survey of Business Competitiveness, a survey with nearly 11,000 respondents, with a rural region over-sample (25% of establishments responding are urban and 75% are rural). We employ a bivariate probit model using as controls a number of establishment-level characteristics for our analysis. A log likelihood ratio test confirms that urban and rural establishments should be modeled separately. While patents may provide a reasonable measure of innovative activity for urban establishments, they are more a problematic measure for rural establishments. We conclude with a brief discussion of implications and study limitations.
Fee Complexity and Investor Mistakes in Retail Financial Markets

Mutual funds sold via brokers offer fund portfolios that investors can purchase in one of three classes: A, B or C. These classes are distinguished only by their fee schedules and thus have different net performance results. An analysis of relative class performances for a set of U.S. mutual funds between 1992 and 2008 reveals a striking fact about class B: while classes A and C provide the best performance results at long and short holding periods, respectively, class B is dominated by either class A or C at any holding period. The inferiority yet popularity of class B at first suggests that naïve investors who do not understand the fee schedule of this class are being exploited. However, I propose two hypothetical clienteles which might rationally demand class B shares: one (a) with uncertain holding periods, or one (b) that desires to have long holding periods but is unable to commit to them. I identify whether investors rationally or naïvely purchase class B by examining the flow-fee sensitivity and estimating investor holding periods. My results support the naïve investor explanation.
MACHINE LEARNING AND IOT FOR SMART GRID

Abstract. The current electricity grid is no longer an efficient solution due to increasing user demand for electricity, old infrastructure and reliability issues requires a transformation to a better grid which is called Smart Grid (SG). Also, sensor networks and Internet of Things (IoT) have facilitated the evolution of traditional electric power distribution networks to new SG, these networks are a modern electricity grid infrastructure with increased efficiency and reliability with automated control, high power converters, modern communication infrastructure, sensing and measurement technologies and modern energy management techniques based on optimization of demand, energy and availability network. With all these elements, harnessing the science of Artificial Intelligence (AI) and Machine Learning (ML) methods become better used than before for prediction of energy consumption. In this work we present the SG with their architecture, the IoT with the component architecture and the Smart Meters (SM) which play a relevant role for the collection of information of electrical energy in real time, then we treat the most widely used ML methods for predicting electrical energy in buildings. Then we clarify the relationship and interaction between the different SG, IoT and ML elements through the design of a simple to understand model, composed of layers that are grouped into entities interacting with links. In this article we calculate a case of prediction of the electrical energy consumption of a real Dataset with the two methods Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM), given their precision performances.
Synergistic combination dry powders for inhaled antimicrobial therapy

Combination products play an important role in medicine as they offer improved clinical effectiveness, enhanced patient adherence, and reduced administrative costs. In combination antimicrobial therapy, the desired outcome is to extend the antimicrobial spectrum and to achieve a possible synergistic effect. However, adverse antagonistic species may sometimes emerge from such combinations, leading to treatment failure. Therefore, it is crucial to screen the drug candidates for compatibility and possible antagonistic interactions. This work aims to develop a novel synergistic dry powder inhaler (DPI) formulation for antimicrobial combination therapy via the pulmonary route. Binary and ternary combinations were prepared via spray drying on a BUCHI® Nano Spray Dryer B-90. All powders were within the respirable size range, and were consisted of spherical particles that were slightly corrugated. The powers yielded fine particle fractions (of the loaded dose) of over 40% when dispersed using an Aerolizer® DPI at.
Research on Vehicle Detection Technology of Blind Spots at Night Based on CAdaBoost Algorithm

Aiming at the problem of vehicle video detection in blind areas at night, a method of vehicle detection in blind areas at night based on CAdaBoost algorithm is proposed. Since night vehicles and daytime vehicles have different illumination, visibility, vehicle edge characteristics, vehicle contours, etc., the test image is first grayed out and ROI is determined. Then, because the features of the car head and wheels at night are more obvious than other features, a parallel method is used to train multiple weak classifiers offline at the same time, mainly to train the Haar-like features of the car head and wheels of the test image. In the meantime, in order to improve the accuracy of detection, the weighted parameter is introduced to determine the role of the weak classifier in the final strong classifier. Then, the offline trained model is used to match the Haar-like features of the test vehicle’s car head and wheels respectively, and finally realize the real-time detection of vehicles in the blind area. The results show that: for vehicle detection in blind spots at night, the algorithm has a high detection accuracy and low detection time.
Laser Imaging in the Stabilisation Region of Turbulent Lifted Flames

The stabilisation region of turbulent lifted flames of methane has been investigated using simultaneous laser imaging of Rayleigh scattering, Raman scattering and OH·LIF. These images are used to derive mixture fraction, temperature, fuel mass fraction and OH concentration images. This enables the mixing field and the reaction zone of the lifted flames to be studied in detail. The images reveal that the oscillation in the lift off height of these flames may be caused by large scale vortices in the fuel jet pushing out into the reaction zone and causing entrainment of ambient coflowing air around the base of the reaction zone subsequently shifting it further downstream. It is proposed that the flame is stabilised through a combination of premixed propagation into fresh mixture and extinction due to the interaction of large scale turbulent structures in the jet. The large scale structures cause extinction by drawing ambient airin the base of the stabilisation region and convecting the reaction zone downstre.
Online measurement of dissolved oxygen in shake flask to elucidate its role on caffeine degradation by Pseudomonas sp.

ABSTRACT Caffeine is a plant alkaloid present in the large ratio over other emerging pollutants and it causes serious health effects on overdosage. Microbial degradation of caffeine produces metabolites that can be used as a multi-functional drug. In this study, the effect of dissolved oxygen (DO) on microbial growth and degradation of caffeine in minimal media, synthetic coffee effluent treatment, and theobromine production was studied in presens flask – SFR vario installed in an orbital shaker. Induction studies showed Pseudomonas sp. requires oxygen for caffeine degradation. Theobromine production with induced cells of Pseudomonas sp. showed maximum accumulation of 35 mg/l with a higher molar yield of 80% at higher DO of 60% saturation when compared to experiments done with a lower oxygen level of 25% and 20% saturation. Effluent treatment using induced cells was the fastest caffeine degradation ever reported at 0.055 g/l.h with 0.4 g/l of induced cell concentration without affecting the polyphenol content significantly. Higher DO in the medium is required for efficient conversion of caffeine to theobromine which is in agreement that the reaction is oxidative demethylation. Online monitoring of DO is very important in shake flask studies which will be useful in scaling up processes.
Eco-Physiological Properties of Open-Field Cucumbers Responded to Organic Liquid Fertilizers

This study was initiated to determine the effect of organic farm-derived liquid fertilizer (LF) on (1) the performance of open-field cucumbers (Cucumis sativus L.) and (2) the soil environment. Treatments included fertigation with a 0.2% solution of an equal T-N concentration on each LF, including long-term non-treatment (LNT, groundwater), non-treatment (NT, groundwater), oil cake (OC), bone meal + fish residue (BF), fish extract + active phosphoric acid (FP), sesame oil (SO), and starfish (SF). Electrical conductivity (EC) in LF was increased in the SF or BF, with high concentrations of T-C observed in the OC and BF and high P in the SO. LNT treatment decreased soil mineral nutrient concentrations and numbers of bacterial operational taxonomic units, invertebrates, and earthworms, significantly increasing infection of powdery mildew and downy mildew for the plants but reducing foliar concentrations of T-N, P, Ca, and SPAD values, and vegetative growth parameters. Soil bulk density decreased in the SF and SO plots. Total fruit yield and fruit yield efficiency were enhanced by BF, FP, SO, and SF treatments, with the highest top grade values observed on the FP- and SO-fruit. Overall, all the organic LF, in particular the SO treatment, would have improved eco-physiological sustainability and provided an alternative organic fertilizer for a short growing period.
A Python script to merge Sanger sequences

Merging Sanger sequences is frequently needed during the gene cloning process. In this study, we provide a Python script that is able to assemble multiple overlapping Sanger sequences. The script utilizes the overlapping regions within the tandem Sanger sequences to merge the Sanger sequences. The results demonstrate that the script can produce the merged sequence from the input Sanger sequences in a single run. The script offers a simple and free method for merging Sanger sequences and is useful for gene cloning.
Canard resonance: on noise-induced ordering of trajectories in heterogeneous networks of slow-fast systems

We analyse the dynamics of a network of semiconductor lasers coupled via their mean intensity through a non-linear optoelectronic feedback loop. We establish experimentally the excitable character of a single node, which stems from the slow-fast nature of the system, adequately described by a set of rate equations with three well separated time scales. Beyond the excitable regime, the system undergoes relaxation oscillations where the nodes display canard dynamics. We show numerically that, without noise, the coupled system follows an intricate canard trajectory, with the nodes switching on one by one. While incorporating noise leads to a better correspondence between numerical simulations and experimental data, it also has an unexpected ordering effect on the canard orbit, causing the nodes to switch on closer together in time. We find that the dispersion of the trajectories of the network nodes in phase space is minimized for a non-zero noise strength, and call this phenomenon canard resonance.
New synthetic routes to synthons for the synthesis of functionalized aspidosperma alkaloids

The diazoketones (3a and b) and the iminomalonates (7a and b) have been converted into the tetracyclic vinylogous amides (6a and b) by an acid-catalysed single-step reaction; Birch reduction of the amides (6a and b) afforded the corresponding tetracyclic ketones (2a and b), synthons for the synthesis of functionalized aspidosperma alkaloids.
Transitional Relations of China and Myanmar: A New Economic Geography Approach to the Mandalay- Ruili Road Connection

This article explores the function of a transnational road in China-Myanmar relations from a perspective that reflects on Myanmar’s experience. The analysis focuses on economic activities at the city level, in order to assess advantages and disadvantages to the relationship between both countries. The cities that were chosen as the units of analysis are Ruili and Mandalay. Using a New Economic Geography approach, a core-periphery pattern was applied as the theoretical framework to explain industrial relocation and agglomeration. In addition, this article also highlights the political and economic transitions in Myanmar since 2010 that led to change in the relational structure. The article makes two key points. Firstly, Myanmar’s dependent relationship with China is illuminated if one applies a New Economic Geography perspective to economic processes. The road played a role in the process by which Ruili was transformed into an industrialized core and Mandalay became an agricultural periphery. Secondly, the core-periphery relation is not static. At least 3 factors from the Myanmar side such as the border situation, forest policy and special economic zone policy that launched after 2011 country’s reformation have impacted the relational structure. The latter point indicates that China’s influence is greatly contested by the smaller country, and that the interaction of economic and political factors impact the Myanmar-China relationship, particularly at local sites.
Attenuation methods for quantifying gas saturation in organic-rich shale and tight gas formations

Quantitative interpretation of waveform attenuation for determining petrophysical properties remains one of the most challenging problems associated with rock physics. In this study, two effective methods are proposed to compute gas saturation in organic-rich shale and tight gas formations from full-waveform sonic attenuations. We first extract compressional (P)- and shear (S)-wave attenuations from monopole and dipole waveforms by median frequency shift and multi-frequency inversion methods, respectively. Crossplots of the P- to S-wave attenuation ratio ([Formula: see text]) and core gas saturation show a positive linear correlation. The [Formula: see text] value and the neutron-density porosity difference exhibit an identical log trend across different formations. The coincidence of these two different hydrocarbon indicators implies that [Formula: see text] is most sensitive to pore-fluid saturation and is less affected by variations in lithology. In the first method, the core-calibrated [Formula: see text] yields an accurate estimate of gas saturation. The second method is suited for the absence of core saturation data, which use the probability distribution of [Formula: see text] for the evaluation of gas saturation. Compared to conventional resistivity methods, the proposed attenuation method, as a nonelectric approach, provides a more accurate gas saturation prediction for low-resistivity reservoir rocks. Finally, we analyze the characteristics of attenuation-saturation relations in low-porosity rocks and discover the possible attenuation mechanisms.
The readability and reliability of Greek web-based information on rhinoplasty

Background: A constantly increasing number of patients seek for Internet sources on diseases or surgical operations before consulting with a medical specialist. Popular among surgical procedures is rhinoplasty. Depending on the quality of information, patient decision making, expectations and satisfaction may be affected in a positive or negative manner. The aim of this study is to objectively assess the readability and reliability of Internet health information in the Greek language on rhinoplasty. Materials and Methods: We performed a search in the Google engine using a combination of Greek language terms relating to rhinoplasty. After collation and rejection of duplicate, irrelevant or invalid links, the first twenty highest ranking Greek Web sites were analyzed using the on-line Greek Language Centre Literacy Level calculator, the on-line Greek text readability calculator, and the DISCERN publication quality assessment instrument. Results: From the twenty Web sites, 40% required very good and 35% required excellent Greek Language Literacy Level for comprehension. Content reading was considered quite difficult in 15%, difficult in 60% and very difficult in 25% of the Web sites. The quality of the Web sites appraised by the DISCERN instrument was low to medium. No correlation was found between Google site rank and DISCERN total score. Conclusions: In general, the reliability of Internet health information in the Greek language on rhinoplasty is mediocre at best and the readability of the respective texts is lower than recommended. Patients should be cautious and always consult one or more medical specialists before reaching a final decision. Evaluation and accreditation of Internet health information sites would greatly assist on sound patient decision-making and satisfaction.
Production of Xylenes from Toluene and 1,2,4-Trimethylbenzene over ZSM-5 and Mordenite Catalysts in a Fluidized-Bed Reactor

The production of various xylenes from toluene, heavy aromatics such as 1,2,4-trimethylbenzene (1,2,4-TMB) and their mixture was investigated over H-ZSM-5 (H-Z), H-mordenite (H-M) and a dual zeolitic catalyst comprising ZSM-5 and mordenite (H-ZM). The experiments were conducted in a riser-simulator reactor under different operating conditions to study the effect of temperature, reaction time and feed composition on conversion and product yields. At 400 °C, the conversion of toluene over the three catalysts yielded mainly benzene and xylenes with maximum conversion at 25 % and a xylene yield of 12.5 wt % over the H-M catalyst. The transformation of 1,2,4-TMB doubled the conversion level and xylene yield and suppressed benzene formation. However, a considerable portion of the 1,2,4-TMB feed was isomerized into 1,2,3-TMB and 1,3,5-TMB accompanied by the formation of tetramethylbenzenes (TeMBs). The conversion of an equimolar mixture of toluene and 1,2,4-TMB over the three catalysts resulted in higher toluene conversion and double xylene yield in comparison with 1,2,4-TMB alone. The advantage of using a dual zeolitic catalyst was observed at an equimolar feed of toluene and 1,2,4-TMB, exhibiting maximum toluene conversion, higher xylene yield and the formation of lower levels of undesirable products.
Electropolymerized Molecularly Imprinted Polymers as Receptor Layers in Capacitive Chemical Sensors

The first application of molecularly imprinted polymers to chemical sensors with capacitive detection is described. The sensitive layer was prepared by electropolymerization of phenol on gold electrodes in the presence of the template (phenylalanine). The insulating properties of the polymer layer were studied by electrochemical impedance spectroscopy. Electrical leakages through the polymer layer were suppressed by deposition of a self-assembled monolayer of mercaptophenol before polymerization and of alkanethiol after polymerization. At the final stage of sensor preparation, the template was removed. The multilayer system obtained displayed a decrease in electrical capacitance on addition of phenylalanine. Only a low response was observed toward other amino acids and phenol.