Miracle-dz/UniFAR-FTUs huggingface dataset:
Convex-transitive characterizations of Hilbert spaces

We investigate real convex-transitive Banach spaces X, which admit a one-dimensional bicontractive projection P on X. Various mild conditions regarding the weak topology and the geometry of the norm are provided, which guarantee that such an X is in fact isometrically a Hilbert space. For example, if uESX is a big point such that there is a bicontractive linear projection P : X → [u] and X* is weak*-locally uniformly rotund, then X is a Hilbert space. The results obtained here are motivated by the well-known Banach—Mazur rotation problem, as well as a question posed by B. Randrianantoanina in 2002 about convex-transitive spaces.
Age, growth and mortality of the thumbprint emperor ( Lethrinus harak ) in Zanzibar

The growth parameters of Lethrinus harak from Zanzibar were studied from 308 samples collected between June 2019 and May 2020 at Unguja Ukuu and Mkokotoni landing sites. Growth rings counted on whole otoliths formed annually, with opaque margins generated in December to February and hyaline rings in March to November. Ring counts revealed that most fish were between three and four years old, with mean lengths of 17.7 and 21.4 cm, respectively. Some specimens were five to seven years old, measuring 24.2 to 28.2 cm, on average. The growth parameters were estimated as L ∞ = 34.22 cm, K = 0.25 year -1 , and t 0 = 0.00. The total mortality ( Z ) was estimated as 0.68 year -1 , natural mortality ( M ) was 0.65 year -1 using Pauly’s equation, and fishing mortality ( F ) was 0.03 year -1 . The low estimate of exploitation rate ( E ) of 0.04 year -1 was almost certainly an underestimate, resulting from the absence of older (>8 years) large individuals, and younger (<3 years) small individuals in samples.
response optimization of

In this study a paper-based analytical device was developed using screen printing technique for the determination of particulate iron from welding fumes. The operational parameters such as volume and concentration of 1,10-phenanthroline, volume and concentration of hydroxylamine were optimized by the Box Behnken Design (BBD) using Minitab. Additionally, the µ-PAD's sample solution holding capacity and reaction time were also optimized. Under the optimized condition, particulate metal concentrations were colorimetrically quantified using a handheld mobile phone and image processing software, ImageJ. Very good analytical performance such as good linearity of the calibration curve and better selectivity was observed by the developed method. The limit of detection for Fe 3+ assay was 4.6 mg/L; which is adequate to determine the threshold concentration limit of particulate iron set by the regulatory bodies (6 mg/L). The µ-PAD revealed 95-99% recovery compared with the UV-Vis spectrophotometry (98-100%). Furthermore, welding fume samples were collected in Addis Ababa over five days, using mixed cellulose ester filters and the findings show a high concentration that exceeds the standard levels. Analyzing particulate iron with µ-PADs yielded results consistent with UV-Vis spectrophotometry, suggesting µ-PADs' potential application for occupational particulate iron exposure measurement, eliminating the need for expensive analytical devices
Network traffic classification based on improved DAG-SVM

Network traffic classification plays a fundamental role in network management and services. Given error accumulation in traditional DAGSVM (Directed Acyclic Graph-Support Vector Machine) algorithm, we propose an improved DAGSVM classification method using two different possibility metrics in this paper. Differing from traditional DAG-SVM, the improved DAG-SVM algorithm eliminates one class only under the condition of that classification error probability is less than threshold. The experiment results show that compared with traditional DAG-SVM, the methods proposed in this paper both have higher classification accuracy with acceptable time cost and improved DAG-SVM based on distance has a better performance than improved DAG-SVM based on decision function.
Vision based victim detection from unmanned aerial vehicles

Finding injured humans is one of the primary goals of any search and rescue operation. The aim of this paper is to address the task of automatically finding people lying on the ground in images taken from the on-board camera of an unmanned aerial vehicle (UAV). In this paper we evaluate various state-of-the-art visual people detection methods in the context of vision based victim detection from an UAV. The top performing approaches in this comparison are those that rely on flexible part-based representations and discriminatively trained part detectors. We discuss their strengths and weaknesses and demonstrate that by combining multiple models we can increase the reliability of the system. We also demonstrate that the detection performance can be substantially improved by integrating the height and pitch information provided by on-board sensors. Jointly these improvements allow us to significantly boost the detection performance over the current de-facto standard, which provides a substantial step towards making autonomous victim detection for UAVs practical.
Nucleic acid-gold nanoparticle conjugates as mimics of microRNA.

Novel conjugates of gold nanoparticles (13±1nm) functionalized with synthetic microRNAs can enter cells without the aid of cationic co-carriers and mimic the function of endogenous microRNAs. These conjugates can regulate multiple proteins through interactions with 3′ untranslated region of the target mRNA and control cell behavior. The conjugates are a promising new tool for studying miRNA function and new candidates for miRNA replacement therapies.
Study on Microbial Community Structures in Drinking Water Sludge by PCR-DGGE

In order to offer useful information for harmless disposal of drinking water sludge, the bacterial community structures of sludge produced in two different drinking water plants were initially studied by polymerase chain reaction–denaturing gradient gel electrophoresis (PCR–DGGE) technique. The result of sequencing of DGGE band analysis showed that the microbial community structure of drinking water sludge was complex, various types and a large number of microbes lived in drinking water sludge according to the Shannon-Wiener index of diversity (H) and the specific richness (R). Nine phyla obtained by the similarity analysis of 27 strong bands selected from the DGGE profiles sludge samples as follows: Proteobacteria, Acidobacteria, Fibrobacteres, Chloroflexi, Bacteroidetes, Firmicutes, Cyanobacteria, Verrucomicrobia and Sheathe bacteria . Among them, Proteobacteria contained two classes ( Gamma-proteobacteria and Beta-proteobacteria ) and then three genera ( Rhodocyclus, Proteobacterium and Methylothermus ) were the most common species. Chloroflexi including three classes ( Chloroflexi , Caldilineae and Anaerolineae ) and Bacteroidetes ( Bacteroidetes and Flavobacteria ) were also usual populations. Most of species, with high organic materials degradation activity, were heterotrophic bacteria due to a large number of organic materials contained in drinking water sludge. The present study also demonstrated the comparison of microbial community structure between drinking water sludge and wastewater sludge, Proteobacteria , Bacteroidete s and Chloroflexi were considered as the most common dominant species on phylum level, Differences such as the number of Rhodocyclu in drinking water sludge or Micrococcus in wastewater sludge were obviously shown due to the different treatment process and the inlet water quality.
Quantification and Distribution of Salmonella spp. and Salmonella typhi in Wastewater Treatment Plants

In order to know about distribution of Salmonella spp. and proportion of Salmonella typhi in raw and treated wastewater, the real-time PCR methods were established and applied to monitoring of influents and effluents from three municipal wastewater treatment plants. Salmonella typhi can be well distinguished from non-typhi Salmonella by using specific primer set. The detection limit is 4.20 copies for Salmonella and 5.28 copies for Salmonella typhi per PCR. Statistical analysis showed that the distributions of Salmonella spp. and Salmonella typhi well followed the log-normal relationship. In influent samples, Salmonella spp. ranged 10 3 ~10 6 copies/100mL, and Salmonella typhi ranged 10 2 ~10 4 copies/100mL. Municipal wastewater treatment process can remove around 1 log unit for Salmonella and 0.5 log units for Salmonella typhi in general. The proportion of Salmonella typhi in Salmonella spp. was under 5% in most raw wastewater samples. The established methods can be usefully used to quantitative detect Salmonella and analyze proportion of Salmonella typhi in wastewater. This is useful to further study on Salmonella transmission in urban water environment and health risk assessment.
Reinventing the Web Browser for the Semantic Web

The paper extends the traditional browser concept with a Semantic Web tailored faceted browser thus providing integrated end-user grade support for both legacy Web and Semantic Web content. The new browser provides interactive exploratory search and navigation capabilities as well as user adaptation and personalization. We describe the operation, usage scenarios and dependencies of the browser.
Smith ScholarWorks Smith ScholarWorks

Stachydrine, a betaine released by germinating alfalfa seeds, functions as an inducer of nodulation genes, a catabolite, and an osmoprotectant in Sinorhizobium meliloti . Two stachydrine-inducible genes were found in S. meliloti 1021 by mutation with a Tn 5-luxAB promoter probe. Both mutant strains (S10 and S11) formed effective alfalfa root nodules, but neither grew on stachydrine as the sole carbon and nitrogen source. When grown in the absence or presence of salt stress, S10 and S11 took up [ 14 C]stachydrine as well as wild-type cells did, but neither used stachydrine effectively as an osmoprotectant. In the absence of salt stress, both S10 and S11 took up less [ 14 C]proline than wild-type cells did. S10 and S11 appeared to colonize alfalfa roots normally in single-strain tests, but when mixed with the wild-type strain, their rhizosphere counts were reduced more than 50% ( P < 0.01) relative to the wild type. These results suggest that stachydrine catabolism contributes to root colonization. DNA sequence analysis identiﬁed the mutated locus in S11 as putA , and the luxAB fusion in that gene was induced by proline as well as stachydrine. DNA that restored the capacity of mutant S10 to catabolize stachydrine contained a new open reading frame, stcD . All data are consistent with the concept that stcD codes for an enzyme that produces proline by demethylation of N -methylproline, a degradation product of stachy-drine.
Passive Driver Gaze Tracking with Active Appearance Models (特集 センシング技術)

Passive gaze estimation is usually performed by locating the pupils, and the inner and outer eye corners in the image of the driver’s head. Of these feature points, the eye corners are just as important, and perhaps harder to detect, than the pupils. The eye corners are usually found using local feature detectors and trackers. In this paper, we describe a passive driver gaze tracking system which uses a global head model, speciﬁcally an Active Appearance Model (AAM), to track the whole head. From the AAM, the eye corners, eye region, and head pose are robustly extracted and then used to estimate the gaze.
Home Range Use and Movement Patterns of Non-Native Feral Goats in a Tropical Island Montane Dry Landscape

Advances in wildlife telemetry and remote sensing technology facilitate studies of broad-scale movements of ungulates in relation to phenological shifts in vegetation. In tropical island dry landscapes, home range use and movements of non-native feral goats (Capra hircus) are largely unknown, yet this information is important to help guide the conservation and restoration of some of the world’s most critically endangered ecosystems. We hypothesized that feral goats would respond to resource pulses in vegetation by traveling to areas of recent green-up. To address this hypothesis, we fitted six male and seven female feral goats with Global Positioning System (GPS) collars equipped with an Argos satellite upload link to examine goat movements in relation to the plant phenology using the Normalized Difference Vegetation Index (NDVI). Movement patterns of 50% of males and 40% of females suggested conditional movement between non-overlapping home ranges throughout the year. A shift in NDVI values corresponded with movement between primary and secondary ranges of goats that exhibited long-distance movement, suggesting that vegetation phenology as captured by NDVI is a good indicator of the habitat and movement patterns of feral goats in tropical island dry landscapes. In the context of conservation and restoration of tropical island landscapes, the results of our study identify how non-native feral goats use resources across a broad landscape to sustain their populations and facilitate invasion of native plant communities.
Seasonal average temperature forecast with the AutoGluonTS modern autoML tool

Forecasting the temperature at a given place in a given future epoch is of evident huge interest. This is extremely hard unless future means “next days”. In this paper, we focus on the problem of forecasting if a given future period (say, next summer) will be hotter than usually. More precisely, the objective is to say if the average daily temperature will be above normal, normal or below normal, where normal is defined on past observed values. For this task, most of the production tools are of the dynamic type (that is, physical, usually huge systems of partial differential equations) or statistical, or a combination of both. In the paper, we explore the use of modern Machine Learning tools and show that they can compete with those dedicated and always heavy and complex procedures, in spite of the fact that our results come from standard tools and hardware. We illustrate the results with data coming from a project where these questions are studied, concerning a large area in the Southern part of South America.
Real-time analysis of data from many sensors with neural networks

Much research has been conducted that uses sensor-based modules with dedicated software to automatically distinguish the user's situation or context. The best results were obtained when powerful sensors (such as cameras or GPS systems) and/or sensor-specific algorithms (like sound analysis) were applied A somewhat new approach is to replace the one smart sensor by many simple sensors. We argue that neural networks are ideal algorithms to analyze the data coming from these sensors and describe how we came to one specific algorithm that gives good results, by giving an overview of several requirements. Finally, wearable implementations are given to show the feasibility and benefits of this approach and its implications.
Convolutional neural networks and microwave-ultrasound data fusion for breast imaging

Breast cancer is most common among females. Different imaging modalities have been investigated for breast imaging, such as X-ray, ultrasound, MRI and microwave. Among them, microwave and ultrasound are non-invasive, non-ionizing and low-cost. Microwave is preferred since providing high-contrast images, yet resolution is low due to the relatively large wavelength; ultrasound can produce high-resolution images with low contrast. Thus, it is of great interest to fuse these two modalities to produce images with both high contrast and high resolution. Fusion can be achieved by simultaneous inversion in the imaging process, or by successive imaging with the result of one modality used as prior in the inversion of another modality, or by fusion of two images after imaging procedure. Here the ﬁrst method is investigated. Several algorithms have been proposed for joint inversion, based on physical or empirical relations between different parameters [1] or on structure similarities [2]. Recently, convolutional neural networks (CNN) have been investigated for inverse scattering problems [3, 4] and have shown great potential. In this work, we use convolutional neural networks (CNN) to achieve joint inversion of microwave and ultrasound. The CNN structure is based on two-stream CNN [5], proposed to utilize both temporal and spatial information as the inputs of two CNNs and then fused by a classiﬁer for video recognition. Similarly, two networks are built for ultrasound and microwave data, resp. , and convolutional kernels shared for these two sets of data after their features are combined at some level. Every pixel of the output image is classiﬁed into a
Gender and Age Wage–Productivity Gaps in Intangible and Non-Gender and Age Wage–Productivity Gaps in Intangible and Non-Intangible Work Occupations Intangible Work Occupations

The paper focuses on gender-and age-related wage–productivity gaps in intangible and non-intangible work occupations using the 2017 Slovenian linked employer–employee microdata for privately owned firms. Comparing employees based on age, gender and occupation, our results show that, in general, there are wage gaps in favour of men, with the exception of individuals aged 50 or older who belong to the intangible capital group, where the wages of men and women are almost equal. There are also significant wage gaps in favour of older workers, with the exception of women in non-intangible occupations, where those aged 30–49 and those aged 50 + earn almost the same. Comparing the productivity of workers using value added decomposition method and based on age, gender and occupation, in general we find that gender and age gaps are more pronounced. For example, women tend to be more productive than men, with the exception of men under the age of 30 in non-intangible work occupations. Similarly, older workers tend to be less productive than their younger counterparts, with the exception of women aged 30–49 compared to women under 30 in non-intangible work occupations. Moreover, age-related wage productivity gaps are higher for intangible than for non-intangible worker occupations.
ARTÍCULO ACEPTADO – PUBLICACIÓN ADELANTADA ACCEPTED ARTICLE – AHEAD-OF-PRINT

This study analyzes the exchange rate pass-through effect on the Consumer Price Index (CPI) in Mexico's main border and 27 non-border metropolitan cities. The period examined includes monthly data from January 2002 to December 2019. A vector autoregressive model (VAR) is used, which includes formal employment at the city level as a proxy to economic development, interest rates, nominal exchange rates, each analyzed city’s CPI, U.S. consumer prices, energy commodity prices and control variables such as service sector employment share and large firm employment share. Impulse response functions are constructed. Results for the 2002-2016 period indicate that exchange rate changes primarily affect border cities. Different arguments are included to justify such results. Pass-through values are also found to increase in general for all cities when the period 2017-2019 (January 2017 when important gasoline price shocks started previous its price liberalization in December 2017) is included in the regressions. JEL Classification: E30, E31, E58, F30, F31.
Tinmith-Metro: new outdoor techniques for creating city models with an augmented reality wearable computer

This paper presents new techniques for capturing and viewing on site 3D graphical models for large outdoor objects. Using an augmented reality wearable computer, we have developed a software system, known as Tinmith-Metro. Tinmith-Metro allows users to control a 3D constructive solid geometry modeller for building graphical objects of large physical artefacts, for example buildings, in the physical world. The 3D modeller is driven by a new user interface known as Tinmith-Hand, which allows the user to control the modeller using a set of pinch gloves and hand tracking. These techniques allow user to supply their AR renderers with models that would previously have to be captured with manual, time-consuming, and/or expensive methods.
Enabling implicit human computer interaction: a wearable RFID-tag reader

Implicit human computer interaction is based on the concept of using user activity in the real world as input to computers. Implicit HCI can help to reduce the problem of user input to wearable computers. In this paper we report on wearable RFID technology that facilitates applications that are triggered by handling tagged physical objects. We also report on a case study in which the technology was integrated with an enterprise resource planning system to optimize work processes that involve physical objects.
Jurnal Penelitian Pendidikan

This study discusses learning music through flashcard media to instill character values in early childhood at the Indonesian Music School (SMI) Semarang, Program Foundation of Music (FOM). There are 3 (three) main character values that will be discussed in this study. They are the value of discipline, the value of independence and the value of curiosity. The research questions of this study are the 3 (three) main character values instilled in early childhood in the Program FOM, SMI Semarang. This study uses an Inculcation Approach. This research uses descriptive qualitative method. In addition, the data collection techniques used in this study were observation, interviews and documentation. From the results of the analysis, it can be concluded that by cultivating 3 (three) main character values; discipline, independence and curiosity, students can implement them and continue to the next stage of development. So that it is in line with the purpose of character education, which is to create superior and dignified student characters.
Improvement of panorama-based annotation overlay using omnidirectional vision and inertial sensors

Annotation overlay on live video frames is an essential feature of augmented reality (AR), and is a well-suited application for wearable computers. A novel method of annotation overlay and its real-time implementation is presented. This method uses a set of panoramic images captured by omnidirectional vision at various points of environment and annotations attached on the images. The method overlays the annotations according to the image alignment between the input frames and the panoramic images. It uses inertial sensors not only to produce robust results of image registration but also to improve processing throughput and delay.
Comparative Study of Thermal Kinetics for Clostridium sporogenes PA 3679 Inactivation using Glass Capillary Tube and Aluminum Tube Methods in Carrot Juice and Phosphate Buffer

Sterilization is one of the most commonly used processing methods in the food industry for the low acid foods. Thermal treatment must be adequate to destroy spores of Clostridium botulinum to ensure the low acid food is microbiologically safe. C. sporogenes PA 3679 spores were used as a surrogate to validate the thermal inactivation methods to control C. botulinum. The objective of this study was to determine the thermal resistance of C. sporogenes PA 3679 in M/15 phosphate buffer (pH 7.0) and carrot juice (pH 6.2) at temperatures of 115.6, 118.3, and 121.1°C using glass capillary tubes and novel aluminum thermal death time (TDT) tubes. Than the differences in come up time and thermal inactivation parameters of C. sporogenes PA 3679 (1.0 x10 7 spores/ml) were compared. In phosphate buffer, D115.6, D118.3 , D121.1 values for glass capillary tubes were 2.60, 1.11, and 0.54 min and for the aluminum TDT tubes 2.20, 1.12 and 0.60 min, respectively. In carrot juice, D115.6, D118.3, D121.1 values were 2.12, 1.32, and 0.69 min for glass capillary tubes and 2.40,1.36, and 0.71 min for the aluminum TDT tubes, respectively. The z-values in phosphate buffer were 8.06°C and 11.27° C, and in carrot juice were 9.75 °C and 10.39°C for capillary tube and aluminum TDT tubes, respectively. The results of this study may be used to design a thermal sterilization process for carrot and carrot containing food products.