Miracle-dz/UniFAR-FTUs huggingface dataset:
Fine-grained recognition of Chinese food image based on DenseNet with attention mechanism

Recently, deep learning convolutional neural network has been widely used in food recognition and other fields, but there are still some problems such as poor semantic feature extraction ability and low recognition accuracy of Chinese food images. Based on the above reasons, this paper proposed a DenseNet model based on attention mechanism for image recognition of Chinese food. Using the idea of transfer learning, this paper applied the DenseNet pre-training model with excellent classification performance to the Chinese food image dataset. In order to improve the ability of extracting distinguishable features and learning fine-grained features of Chinese food images, this paper proposed an attention mechanism based on the DenseNet-169 model. This paper used the attention module to extract the key semantic feature map of the image, and then carried out the adaptive multi-fine-grained region tailoring. Finally, based on the region weight fusion scheme, the multi-fine-grained region feature map was integrated into an image feature description and sent to DenseNet-169 for recognition, so as to realize the end-to-end image recognition network. Experiments were carried out on VIREO Food-172 dataset, and the results shows that our method achieves considerable and comparable recognition performance to the state-of-art.
What We Bring With Us: Investing in Latinx Students Means Investing in Families

The educational landscape of the United States has shifted as more low-income, first-generation Latinx students enroll in 4-year universities. Despite this, many underlying structures and practices of these institutions still reflect the cultural norms of culturally dominant groups (e.g., White, upper-to-middle-class, continuing-generation), privileging individualism. This overlooks the cultural values of low-income, first-generation Latinx students, who often prioritize interdependent connections and obligations. When universities do not recognize familial obligations, students must decide between helping family or doing well in school—which complicates their capacity to succeed academically. To graduate diverse future leaders and build a diverse workforce, educators and policymakers must consider that investing in students means investing in their families, too. Concrete examples, from small interventions to large-scale policy changes, illustrate meaningful investment strategies.
Lattice Monte Carlo Simulations of the Gyroid Phase in Monodisperse and Bidisperse Block Copolymer Systems

Lattice Monte Carlo (MC) simulations in the NVT ensemble together with a coarse-grained model of the block copolymer chains are used to explore the phase diagram of pure and bidisperse diblock copolymer melts as a function of temperature and block volume fraction. In the pure systems, we found that the gyroid phase is stable in only a narrow region of the phase diagram. Through the analysis of the structure of the channels and nodes formed by the minority component in the gyroid phase, we found evidence of “packing frustration” of the chains inside each such node, manifested as a central low-density region. The use of chain-length bidispersity was then investigated as a way to reduce such packing frustration in the gyroid phase. We found that the longer chains in such systems tend to segregate preferentially inside the gyroid nodes. For a system with components with a 2:1 ratio of chain lengths, we observed an increased range of temperatures where the gyroid phase is stable.
Phosphorescent organic light‐emitting diodes using an iridium complex polymer as the solution‐processible host material

We prepared an iridium polymer complex having 2-phenylpyridine as a η2-cyclometallated ligand, a new OLED containing a solution-processible iridium polymer as a host, and a phosphorescent iridium complex, [Ir(piq-tBu)3] as a guest. This is the first example to apply a phosphorescent iridium complex polymer to a host material in a phosphorescent OLED. A phosphine copolymer ligand made from methyl methacrylate (MMA) and 4-styryldiphenylphosphine can be used as an anchor polymer, which coordinates to luminescent iridium units to form a host metallopolymer easily. The OLED containing the host iridium-complex polymer film, in which the guest, 2 wt % Ir(piq-tBu)3, was doped, showed red electroluminescence as a result of efficient energy transfer from the iridium polymer host to the iridium guest. The maximum current efficiency of the device was 1.00, suggesting that a soluble iridium complex polymer can be used as a solution-processible polymer host in EL devices. © 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 47: 4358–4365, 2009
Ammonolyse des Trimetaphosphats

Das Trimetaphosphation reagiert bei 27° C mit wasrigem Ammoniak schnell und weitgehend bei pH ∼ 12. Das erste Produkt ist das Monoamidotriphosphation (O3P · O · PO2 · O · PO2NH2)4−, welches als Dibariumsalz gefallt und isoliert werden kann. Magnetische 31P-Kernresonanzspektra zeigen bei hoher Auflosung, das die Amidotriphosphationen in Losung drei Arten von P-Gruppen besitzen, namlich endstandiges und mittelstandiges PO4 und endstandiges PO3NH2. In alkalischen Papierchromatogrammen hat das neue Anion einen Rf-Wert zwischen dem des Orthophosphats und dem des Trimetaphosphimats. Chromatographie des angesauerten Monoamidotriphosphats deutet darauf hin, das die NH2-Gruppe unter diesen Bedingungen als NH4+-Ion freigesetzt wird und die verbleibende Phosphatkette zur Struktur des Trimetaphosphatrings zuruckkehrt. The trimetaphosphate ion reacts rapidly and extensively at 27° C with aqueous ammonia at pH values near 12. The initial product is the monoamidotriphosphate ion (PO3 · O · PO2 · O · PO2NH2)−4, which can be precipitated and isolated as the dibarium salt. High resolution 31P magnetic resonance spectra show that the amidotriphosphate ions in solution contain three kinds of phosphorus groups (end PO4, middle PO4, and end PO3NH2). In alkaline paper chromatograms the new species has an Rf value between those of orthophosphate and trimetaphosphimate. Chromatography of acidified monoamidotriphosphate indicates that under these conditions the amide group is released as ammonium ion and the phosphorus returns to trimetaphosphate ion.
An in situ investigation of the corrosion behaviour of a weathering steel work of art

An in situ investigation of the atmospheric corrosion phenomena affecting weathering steels has been performed on a large outdoor sculpture dated back to 1983, the ‘Reditus ad origines’ by Agapito Miniucchi. The sculpture is exposed in the Scientific and Technological Pole of the University of Ferrara, and is an interesting example of architectural recovery of an industrial area. The assessment of the corrosion behavior was performed by means of an in situ, nondestructive approach based on electrochemical impedance spectroscopy measurements. The ultimate goal is to understand the corrosion mechanisms that affect outdoor immovable metallic artefacts to develop tailored and long‐lasting conservation strategies. The impedance measurements were carried out by means of a portable equipment specifically designed by the authors to work as a stand‐alone device connected to a personal computer. Polymeric electrodes were employed instead of the traditional electrochemical cell to avoid any acceleration of the corrosion process; the applied stimulus was in the range 0.001 Hz–100 kHz, while the measurement range could span from about 100 Ω to 1 G Ω. Furthermore, chemical analyses were carried out by means of X‐ray photoelectron spectroscopy on samples obtained with a microsampling technique to correlate the electrochemical impedance spectroscopy results with the chemical composition of the corrosion layer and to identify the presence of electrochemically active species. Copyright © 2011 John Wiley & Sons, Ltd.
Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices

Major depressive disorder (MDD) is the leading cause of disability worldwide. Neurofeedback training has been suggested as a potential additional treatment option for MDD patients not reaching remission from standard care (i.e., psychopharmacology and psychotherapy). Here we systematically reviewed neurofeedback studies employing electroencephalography, or functional magnetic resonance-based protocols in depressive patients. Of 585 initially screened studies, 24 were included in our final sample (N = 480 patients in experimental and N = 194 in the control groups completing the primary endpoint). We evaluated the clinical efficacy across studies and attempted to group studies according to the control condition categories currently used in the field that affect clinical outcomes in group comparisons. In most studies, MDD patients showed symptom improvement superior to the control group(s). However, most articles did not comply with the most stringent study quality and reporting practices. We conclude with recommendations on best practices for experimental designs and reporting standards for neurofeedback training.
Enhanced water permeation of reverse osmosis through MFI-type zeolite membranes with high aluminum contents

MFI-type zeolite membranes with different Si/Al ratios were synthesized by seeding and secondary growth. Several factors including alkalinity, synthesis time, and Si/Al ratio were varied to optimize the synthesis conditions. Ion separation of 0.10 M NaCl solution by zeolite membranes was investigated through a cross-flow reverse osmosis system. The aluminum content was found to play an important role in zeolite growth and reverse osmosis separation performance afterward. Membrane hydrophilicity and surface charge measured by the contact angle and particle ζ-potential were found to be strongly dependent on the aluminum composition of the membranes. Both water flux and ion rejection increased considerably as aluminum ions were incorporated into the zeolite framework with a water flux increase from 0.112 to 1.129 kg/m2·h and ion rejection improvement from 90.6% to 92.9%. The enhancement in ion separation and water flux for high aluminum ZSM-5 membranes was further analyzed by enhanced water affinity on the m.
Black Carbon Measurement using Laser Integrating Plate Method

An intensive study to test and validate the Laser Integrating Plate Method (LIPM) of determining absorption coefficient and black carbon mass was carried out. Measurements by LIPM were compared to Smoke Stain Reflectometer measurements and Mie calculations based on accelerator ion beam analysis (IBA) elemental composition measurements. Results show that the value of mass absorption coefficient ϵ = 10 m2g− 1 previously used for mass determination, and widely accepted for black carbon generated by combustion processes, is an inappropriate choice for the type of carbon measured in Sydney. A value of ϵ = 7 m2g−1 for soot and ambient aerosol particles was found to be more appropriate.
Comparison of a statistical-mechanics based plasticity model with discrete dislocation plasticity calculations

A novel, nonlocal version of continuum crystal plasticity theory is proposed, which is based on a statistical description of dislocations. It involves a set of evolution equations for the dislocation density and for the sign-dislocation density, which are coupled to the continuum slip description. The theory is applied to the problem of shearing of a two-dimensional composite material. The results are compared, in qualitative manner, to the results of recent discrete dislocation predictions of the same problem. The new theory is shown to be able to pick up the distinct dependence on particle morphology and the associated size dependence.
Multiconfigurational self-consistent field linear response for the polarizable continuum model: Theory and application to ground and excited-state polarizabilities of para-nitroaniline in solution

This paper presents the linear response (LR) function for a multiconfigurational self-consistent field (MCSCF) molecular wave function for the integral equation formalism version of the polarizable continuum model (PCM). Both equilibrium and nonequilibrium PCM solvation schemes are described: The nonequilibrium scheme is applied to the calculation of excited state wave functions (Franck–Condon states) and/or of dynamic response properties. An important characteristic of the LR-PCM-MCSCF theory is the explicit inclusion of the effects of solvent dynamics, and this allows us to treat a large variety of time-dependent phenomena. Here, in particular, the theory is applied to the study of the solvent effect on transition energies and on static and dynamic polarizabilities of para-nitroaniline (pNA). The study of the polarizability dispersion of pNA is performed for the ground state and for low-lying electronic excited states including the charge transfer state. We compare our results with available experimenta.
On the Adsorption of Chiral Propylene Oxide onto Pd(111): A DFT Study

The adsorption of chiral propylene oxide onto a Pd(111) single crystal was studied via ab initio calculations based on plane-wave Density Functional Theory. Different adsorption sites and different molecular configurations, both tilted and flat, have been analyzed. The on-top site is the preferred one for all configurations. The adsorption energy varies over a wide range of values spanning the range from ca. 10–20 kcal/mol for both the inclination of the molecule with respect to the surface and the coverage.
A Content Filtering from Spam Posts on Social Media using Weighted Multimodal Approach

The system for filtering spam posts on social media is preferred to obtain the relevant content and expected by users. The previous works on spam detection have been done to filter irrelevant content on email and social media based on text or image separately. Due to the social media posts are commonly in the form of image, text, or both, the multimodal data is preferred to improve the capability of system in handling filtering content on social media. In addition, a spam post containing multimodal data sometimes does not indicate spam in both data but only one. To improve the performance of system, we propose a weighted multimodal approach for filtering content from spam posts in social media using Convolutional Neural Network (CNN). The mechanism of weighted multimodal is by weighting of spam prediction results from image and text data. We also investigate the performance of CNN architectures for spam post detection that are 3-layer, 5-layer, AlexNet and VGG16. The performance of each architectures is evaluated by 8000 Indonesian posts in the form of image and text taken from Instagram posts. The results show that the highest accuracy achieves 0.9850 based on the combination of image and text by using a 5-layer architecture. The average accuracy of all CNN architectures using multimodal data is higher than only using image and text data separately.
Inverted pendulum on a cart pneumatically actuated by means of digital valves

This paper deals with an inverted pendulum mounted on a sliding cart pneumatically actuated. Low cost digital pneumatic valves driven by PWM technique are used. The control system uses three nested PID regulators: the inner one controls the force imposed by the pneumatic actuator and the other two control the inclination of the pendulum and the position of the cart. The numerical model of the mechanical and pneumatic system is here shown, with also some first results.
Reproductive tract microbiota of women in childbearing age shifts upon type of gynecological infections and phase in physiological cycle

Background: The association of the normal physiological cycle to the structural pattern of microbiota in reproductive tract of women at reproductive age has not been extensively explored. This study was undertaken to determine whether the vaginal microbes of women at childbearing age is different among groups defined by urogenital tract infections, childbearing history and menstrual cycle, respectively.Results: This was a multiple case-control study of women at childbearing age who were assigned to case or control groups according to their states of urogenital tract infections. The participants were also grouped by childbearing history and menstrual cycle. Samples of vaginal swabs were collected and stored at -70℃ until assayed. The V3-V4 regions of 16S rRNA genes were amplified using PCR and sequenced on the Illumina MiSeq platform. We tested the hypothesis of whether the relative abundance of microbial species in vaginal microbiota was different between women with different urogenital tract infections, childbearing history and menstrual cycle. We showed that the vaginal microbial richness(Alpha diversity measured by PD_whole tree) was decreased in normal women(without reproductive tract infections) than in those with bacterial vaginosis (BV), and decreased in pregnant women than in other groups of non-pregnancy. Similarly, women from groups of normal and in pregnancy had lower beta diversity on measure of unweighted_unifrac distance in comparison to those of uninfected and non-pregnant. The top 10 genus relative abundance, especially that Lactobacillus was the most dominant genus with the relative abundance of 71.55% among all samples, did not differ significantly between groups of childbearing history and menstrual cycle analyzed by ANOVA and nonparametric kruskal_wallis. Lactobacillus iners and Lactobacillus helveticus have the most abundance, totally account for 97.92% relative abundance of genus Lactobacillus. It is proposed that a higher L.helveticus/L.iners ratio is more likely to present in normal women than in the infected and in pregnant than in non-pregnant, although this comparison lacks statistical significance.Conclusions: The relative abundance of dominant bacterial taxa in vaginal microbial communities of women at childbearing age, characterized with 16S rRNA gene sequence and QIIME based analysis, were not different among groups of childbearing history and menstrual cycle. Women from groups of in pregnancy and without reproductive tract infections had lower alpha and beta diversity. The compositional ratio of the main lactobacillus species may shift depending on the normal physiological cycle and reproductive tract infections.
EMI Lecturers’ Training Needs: Towards the Construction of a Measurement Instrument

English-medium instruction (EMI) is a relatively new phenomenon that has come to the fore in most higher education institutions (Dafouz and Smit 2019). It is spreading in an unprecedented manner and increasingly gaining ground globally. At the micro-level, lecturers are key stakeholders since they are the driving force in implementing EMI in the classroom. EMI lecturing involves more than delivering content through English; it is a complex process that requires pedagogical and methodological attention (Cots 2013; Fortanet-Gómez 2013; Morell 2018). Thus, to lecture successfully in EMI contexts, it is important to provide lecturers with specific training. Against this backdrop, the present study addresses EMI lecturers’ training needs, a relatively unexplored aspect (Fenton-Smith et al. 2017; Macaro 2018; Beaumont 2020). This study reports on the adequacy of a survey to explore lecturers’ EMI training needs and on the preliminary results derived from its administration to a group of EMI lecturers at a Spanish university. Findings revealed the suitability of the survey items to identify EMI lecturers’ training needs. Specifically, the findings indicated that, in general, EMI training courses should deal mainly with communication and language use, and pedagogy.
Quantization-Guided Training for Compact TinyML Models

We propose a Quantization Guided Training (QGT) method to guide DNN training towards optimized low-bit-precision targets and reach extreme compression levels below 8-bit precision. Unlike standard quantization-aware training (QAT) approaches, QGT uses customized regularization to encourage weight values towards a distribution that maximizes accuracy while reducing quantization errors. One of the main benefits of this approach is the ability to identify compression bottlenecks. We validate QGT using state-of-the-art model architectures on vision datasets. We also demonstrate the effectiveness of QGT with an 81KB tiny model for person detection down to 2-bit precision (representing 17.7x size reduction), while maintaining an accuracy drop of only 3% compared to a floating-point baseline.
Phytosociological observations on tree species diversity of an urban tropical dry deciduous forest of central India

We analyzed phytosociological characteristics of a tropical dry deciduous forest located in an urban environment of Indian Institute of Forest Management (IIFM) Campus in the capital city of Bhopal of Madhya Pradesh state, Central India. A Comparison has been made among the tree community characteristics during the years 1988, 2002 and 2020 in terms of tree species composition, stem density, basal area and Importance Value Index (IVI). At the time of establishment of the institute in 1988, the forest area resembleda degraded dry scrubland. Due to continuous care/protection, plantation activities, degraded forest recovered remarkably, ecological processes evolved favorably with canopy cover reaching over 60% in some patches and about 50% in general over most part of the campus. During last two decades, tree density increased from 319 to 525 stem ha-1 indicating an increase of 64% whereas basal area increased from 18470.79 cm2 ha-1 to 29782.31 cm2 ha-1,an increase of about 61%. Leguminaceae family represented 26.4% of the tree community followed by Combretaceae (11.76%). Shannon-Weiner index (1.31), Simpson index (0.93) and evenness index (0.85) are within the reported ranges for similar forest type of dry deciduous nature in India. Theresults of the presentstudy will help forest managers in conservation planning of urban tropical forest ecosystem of central India.
VergeDB: A Database for IoT Analytics on Edge Devices

The proliferation of Internet-of-Things (IoT) applications requires new systems to collect, store, and analyze time-series data at an enormous scale. We believe that meeting these scaling demands will require a signiﬁcant amount of data processing to happen on edge devices. This paper presents VergeDB, a database for adaptive and task-aware compression of IoT data that supports complex analytical tasks and machine learning as ﬁrst-class operations. VergeDB serves as either a lightweight storage engine that compresses the data based on downstream tasks or as an edge-based database that manages both compression and in-situ analytics on raw and compressed data. By optimizing for available computation resources, storage capacity, and network band-width, VergeDB will take decisions to maximize throughput, data compression, and downstream task accuracy.
Efficient Full System Memory Tracing with Simutrace GI Fachgruppentreffen Betriebssysteme (BS) 2014

Depending on the intended use of a trace, the type and number of collected events and properties vary. Memory traces, that is recordings of a processor’s memory accesses, leap out. While they proved to be very effective for driving memory hierarchy simulations [7, 8, 10, 11, 12, 13, 16, 17] or gathering statistics about an application’s memory access patterns [14, 18], memory traces pose an extraordinary demand on the tracing components. This is due to the fact that the rate at which new events are generated—i.e., the rate at which the processor accesses main memory—is inherently higher than the rate of function calls, MPI messages or other system events that are typically recorded. Memory traces thus quickly become very large in size, consuming gigabytes of storage. A Linux virtual machine (VM) running a minimal Linux kernel build for instance produces approximately 145 billion trace entries. The same system completing the Postmark benchmark from Phoronix Test Suite [2] even generates around 175 billion write events alone. Memory traces therefore heavily depend on an efficient encoding, a scalable trace format and a tracing mechanism that is capable of dealing with a high rate of incoming events.