Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphometrical Analysis of Dry Adult Human Hip Bones by Coxal Index

Background: The hip bone is one of the most useful skeletal elements in adult skeleton for sex determination. Hip bone may be used even when fragmentary for both medico legal and archaeological purposes. The aim of the present study is to measure few morphometric parameters of various hip bones and to assess these values both side wise and gender wise. Method: The present study was conducted in department of Anatomy, Yenepoya Medical College, Mangalore. 100 adult dry human hip bones were included in the study, of which 50 were male and 50 were female hip bones. 50 bones belonged to right side and 50 to left side. The morphometrical parameters measured were length, width and weight of the hip bones. Coxal index was also calculated. Result: Range, mean, median, standard deviation and standard error of mean were determined for each parameter. Conclusions were drawn after comparing the values with series of other workers. Conclusion: The values were slightly higher on the left side compared to the bones of the right side and also the values were more in male bones compared to female bones. The study would help the forensic experts and the anthropologists in specimen identification and sex determination from skeletal remains. It would also be valuable for the anatomists and the orthopedicians in their respective fields. Keywords: Hip bone, morphometry, coxal index, sexual dimorphism, hip bone weight.
AlgaeMAp: Algae Bloom Monitoring Application for Inland Waters in Latin America

Due to increasing algae bloom occurrence and water degradation on a global scale, there is a demand for water quality monitoring systems based on remote sensing imagery. This paper describes the scientific, theoretical, and methodological background for creating a cloud-computing interface on Google Earth Engine (GEE) which allows end-users to access algae bloom related products with high spatial (30 m) and temporal (~5 day) resolution. The proposed methodology uses Sentinel-2 images corrected for atmospheric and sun-glint effects to generate an image collection of the Normalized Difference Chlorophyll-a Index (NDCI) for the entire time-series. NDCI is used to estimate both Chl-a concentration, based on a non-linear fitting model, and Trophic State Index (TSI), based on a tree-decision model classification into five classes. Once the Chl-a and TSI algorithms had been calibrated and validated they were implemented in GEE as an Earth Engine App, entitled Algae Bloom Monitoring Application (AlgaeMAp). AlgaeMAp is the first online platform built within the GEE platform that offers high spatial resolution of water quality parameters. The App benefits from the huge processing capability of GEE that allows any user with internet access to easily extract detailed spatial (30 m) and long temporal Chl-a and TSI information (from August 2015 and with images every 5 days) throughout the most important reservoirs in the State of São Paulo/Brazil. The application will be adapted to extend to other relevant areas in Latin America.
International articles and finance journal rankings

ABSTRACT This study analyzes the impact of international articles on the reputation of finance journals. The association between journal rankings and geographical contents is examined by focusing on two citation-based indicators and two ranking methods using expert opinions. The results clearly indicate that the four methodologies are correlated with a strong preference for articles focusing on the United States. They also show that international topics are often associated with lower journal rankings. Although articles with a global or European scope do not seem to affect journal reputation, contents focusing on world regions such as Asia or Africa are often correlated with lower journal visibility. These results suggest that the strong emphasis placed by scholars on top-ranked finance journals may conflict with the internationalization of business education.
Ethno-Botanical / Ethno-Medicinal Survey of Folklore Plants in Villages of Durg District in Chhattisgarh State (India)

Durg district is rich in biodiversity of medicinal plants. The forest area is about 08.95 % of the total area of Chhattisgarh. More than 80 villages are found in the range of Durg district. Peoples of villages as well as rural areas are frequently used many plants for the treatment of various diseases by own traditional knowledge. An ethno-botanical / ethno-medicinal survey was under taken to collect the folk knowledge of the inhabitants of the different villages of Durg district. Taxonomically, the plants used by the villagers of this area were classified under 66 families of angiosperms including 192 medicinal plants. The various plant part used included whole plants, leaves, stems, roots, tubers, barks, resin, latex, flowers, fruits and seeds. Botanical name, local name, families and uses in different diseases are given parenthetically.
Pressure–Temperature Phase Diagram of Ta-H System up to 9 GPa and 600 °C

High-pressure hydrogenation behaviors of pure metals have not been investigated extensively, although intense research of hydrogenation reactions under high pressure has been conducted to find novel functional hydrides. The former provides us with valuable information for the high-pressure synthesis of novel functional hydrides. A pressure–temperature phase diagram of the Ta–H system has been determined using the in situ synchrotron radiation X-ray diffraction technique below 9 GPa and 600 °C in this study. At room temperature, the phase boundary obtained between distorted bcc TaH~1 and hcp TaH~2 was consistent with the previously reported transition pressure. The experimentally obtained Clapeyron slope can be explained via the entropy change caused by hydrogen evolution from TaH~2.
Climatic Variables Differentially Influence Neotropical Plant Species of Conservation Concern

ABSTRACT Knowing how and to what extent environmental parameters affect threatened species facilitates the understanding of their specific microhabitat requirements. In this study, we examined the response patterns of four threatened tropical plant species to variations in temperature, precipitation, and physiographic variables, and analyzed the relative contributions of environmental variables to the observed distributions of the species. The studied species are Bursera coyucensis, Cryosophila argentea, Guatteria anomala, and Vatairea lundellii and are cataloged into specific risk categories in the Mexican Official Standard NOM-059-SEMARNAT. Our findings suggest differences in ranges of temperature and precipitation (for example, C. argentea exhibited narrower ranges compared to G. anomala and V. lundellii in precipitation) and similarity in ranges of slope across species distributions. We also found that most species distributions respond non-linearly to variations in environmental variables. These results contribute to defining the environmental spaces of these species. The partial and combined effects of climatic variables, and the range of environmental distributions reported here, have intrinsic implications for the adaptation capacity, plasticity, and survival of these species to environmental variation. This information could be useful to promote conservation activities such as the creation of microhabitats with optimal environmental preferences through sustainable silviculture.
PENGEMBANGAN FORMULASI MIKROEMULSI MINYAK SEREH (Cymbopogon nardus) MENGGUNAKAN EMULGATOR SURFAKTAN NONIONIK

Citronella oil (Cymbopogon nardus) is an essential oil which useful as an antibacterial that is usually provided in the form of macroemulsion for topical use. absorption of macroemulsion through the skin relatively low, thermodynamically is not stable and can produce a separate phase in the storage period. The one of development emulsion system to get better characteristics is to form a microemulsion. Microemulsion is an oil and water dispersion stable thermodynamically stabilized by surfactants and in some cases a cosurfactant. The objective of this study was to formulatecitronella oil in the form of a stable microemulsion using nonionic surfactant. Optimization of the type and amount of emulsifier (surfactant) was required to formulate a stable microemulsion. In this study, microemulsion was evaluated during a month. Type and concentration of surfactant, cosurfactant, Citronella oil (Cymbopogon nardus) and water was optimized. A stable citronella oil microemulsion was successfully created with composition of 15% PEG 400 as cosurfactant, 15% tween 80 as surfactant, 2-4% Citronella oil as oil phase and 10% glycerin as humectant and distilled water as aqueous phase. From the observation, microemulsion formula has clear appearance but physically unstable during a month storage
Evaluating an Educational Intervention Designed to Foster Environmental Citizenship among Undergraduate University Students

Taking its primary interest in active environmental citizenship, this paper aims at evaluating a case of an educational intervention designed to foster environmental citizenship among undergraduate students at a technological university. The study employs a survey methodology implementing a recently validated environmental citizenship questionnaire. A randomized pre-group –post-group quasi-experimental survey design explores students’ environmental citizenship attributes before and after the intervention course, ‘Sustainable Development’, in comparison to students who participated in a general elective course, ‘Media Philosophy’. The results show that the participation in the intervention course induced positive change in students’ environmental citizenship in comparison to the control group. Additional analysis indicates that environmental citizenship is significantly related to environmental attitudes, nature experiences during childhood and adolescence, and gender. The article provides a timely contribution shedding light on how specific pedagogical approaches in higher education can foster environmental citizenship.
Peningkatan Usaha dan Inovasi pada Industri Kecil dan Menengah (IKM) Produk Mekaya Losarang Kabupaten Indramayu

Manajemen inovasi merupakan alat yang digunakan oleh manajer maupun organisasi atau perusahaan untuk mengembangkan produk dan inovasi organisasi atau dengan kata lain manajemen inovasi adalah pengelolaan dan pengorganisasian sebuah proses. Melalui pengabdian masyarakat dan pengembangan, perusahaan melakukan respons terhadap kesempatan eksternal atau internal dan menggunakan upaya kreatif untuk memperkenalkan ide-ide baru, proses atau produk. Untuk menunjang proses pemasaran produk sambal ikan lele pada Industri Kecil dan Menengah (IKM) Mekaya, tim menggunakan metode teknologi digital marketing atau pemasaran online dengan menggunakan media sosial seperti Facebook, WhatsApp, Instagram, dan sebagainya. Selain menggunakan media online tim juga menggunakan media offline dengan melakukan dan mengikuti acara festival dan pameran agar produk sambal ikan lele tersebut banyak diketahui dan dikenal oleh masyarakat. Metode teknologi digital marketing yang akan diimplementasikan untuk proses pemasaran produk sambal ikan lele menggunakan metode partisipatif. Program kegiatan yang dilaksanakan di Industri Kecil dan Menengah (IKM) Mekaya dengan membantu dalam proses pemasaran produk sambal ikan lele (SALE) melalui media sosial dan pemasaran door to door mendapatkan hasil yang cukup memuaskan, sehingga produk tersebut sekarang banyak dikenal dan diketahui oleh masyarakat. Selain membantu dalam pemasaran online, tim juga berhasil melakukan pemasaran offline yaitu dengan mengikuti acara festival atau pameran yang dilaksanakan di Pasar Baru Indramayu selama dua hari. Dengan meningkatnya omset penjualan, yang biasanya proses produksi dilakukan satu bulan sekali, kini proses produksi meningkat menjadi dua kali dalam sebulan. Dengan adanya label pengiriman, produk sambal ikan lele dalam proses pengiriman ke luar kota menjadi lebih teratur dan rapi. Hal ini karena produk kini memiliki identitas tersendiri sebagai pembeda dari produk pesaing. Hal itu juga merupakan salah satu cara untuk menarik minat konsumen karena produk dapat dikemas dengan baik.
High Power Magnetic Field Energy Harvesting through Amplified Magneto‐Mechanical Vibration

Internet of Things (IoT) is driving the development of new generation of sensors, communication components, and power sources. Ideally, IoT sensors and communication components are expected to be powered by sustainable energy source freely available in the environment. Here, a breakthrough in this direction is provided by demonstrating high output power energy harvesting from very low amplitude stray magnetic fields, which exist everywhere, through magnetoelectric (ME) coupled magneto‐mechano‐electric (MME) energy conversion. ME coupled MME harvester comprised of multiple layers of amorphous magnetostrictive material, piezoelectric macrofiber composite, and magnetic tip mass, interacts with an external magnetic field to generate electrical energy. Comprehensive experimental investigation and a theoretical model reveal that both the magnetic torque generated through magnetic loading and amplification of magneto‐mechanical vibration by ME coupling contributes toward the generation of high electrical power from the stray magnetic field around power cables of common home appliances. The generated electrical power from the harvester is sufficient for operating microsensors (gyro, temperature, and humidity sensing) and wireless data transmission systems. These results will facilitate the deployment of IoT devices in emerging intelligent infrastructures.
Evidence for the 3D Radiative Effects of Boundary‐Layer Clouds From Observations of Direct and Diffuse Surface Solar Fluxes

Numerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct‐diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. The direct‐beam calculation takes careful account of the field‐of‐view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct‐diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam.
Coupling of swelling, internal stress evolution, and diffusion in coal matrix material during exposure to methane

We construct theoretical models for time‐dependent swelling of coal matrix material upon adsorption of a single gas, taking into account a coupling between stress, strain, chemical potential, and diffusion. Two models are developed. The first (model A) corresponds to diffusion and hence swelling rates being controlled by the jump frequency of adsorbed molecules between closely spaced adsorption sites and the second (model B) to transport controlled by diffusion of unadsorbed molecules through diffusion paths linking distant adsorption sites. To test these models, we performed axial swelling experiments on a single 4 mm sized cylindrical sample of medium volatile bituminous coal, exposed to CH4 at pressures up to 40 MPa, at 40°C, using 1‐D, high‐pressure dilatometry. The models were calibrated to the experimental data by adjustment of a single‐valued diffusion coefficient, independent of gas pressure and adsorbed concentration. The results show that the data can be accurately explained only by model B. The implication is that the gas transport, the associated adsorption, and hence time‐dependent swelling are controlled by the diffusion of unadsorbed molecules and not by molecules jumping between the adjacent adsorption sites. Our model describes a full coupling between stress, strain, sorption, and diffusion in coal matrix material in terms of parameters that have clear physical meaning and are easily obtained from sorption and swelling experiments on coal of any rank exposed to any gas. It therefore offers an important tool for modeling permeability evolution with time during (enhanced) coalbed methane operations.
The mathematics of erythema: Development of machine learning models for artificial intelligence assisted measurement and severity scoring of radiation induced dermatitis

Although significant advancements in computer-aided diagnostics using artificial intelligence (AI) have been made, to date, no viable method for radiation-induced skin reaction (RISR) analysis and classification is available. The objective of this single-center study was to develop machine learning and deep learning approaches using deep convolutional neural networks (CNNs) for automatic classification of RISRs according to the Common Terminology Criteria for Adverse Events (CTCAE) grading system. Scarletred Vision, a novel and state-of-the-art digital skin imaging method capable of remote monitoring and objective assessment of acute RISRs was used to convert 2D digital skin images using the CIELAB color space and conduct SEV* measurements. A set of different machine learning and deep convolutional neural network-based algorithms has been explored for the automatic classification of RISRs. A total of 2263 distinct images from 209 patients were analyzed for training and testing the machine learning and CNN algorithms. For a 2-class problem of healthy skin (grade 0) versus erythema (grade [≥] 1), all machine learning models produced an accuracy of above 70%, and the sensitivity and specificity of erythema recognition were 67-72% and 72-83%, respectively. The CNN produced a test accuracy of 74%, sensitivity of 66%, and specificity of 83% for predicting healthy and erythema cases. For the severity grade prediction of a 3-class problem (grade 0 versus 1 versus 2), the test accuracy was 60-67%, and the sensitivity and specificity were 56-82%, 35-59%, and 65-72%, respectively. For estimating the severity grade of each class, the CNN obtained an accuracy of 73%, 66%, and 82%, respectively. Ensemble learning combines several individual predictions to obtain a better generalization performance. Furthermore, we exploited ensemble learning by deploying a CNN model as a meta-learner. The ensemble CNN based on bagging and majority voting shows an accuracy, sensitivity and specificity of 87%, 90%, and 82% for a 2-class problem, respectively. For a 3-class problem, the ensemble CNN shows an overall accuracy of 66%, while for each grade (0, 1, and 2) accuracies were 0.76%, 0.69%, and 0.87%, sensitivities were 0.70%, 0.57%, and 0.71%, and specificities were 0.78%, 0.75%, and 0.95%, respectively. This study is the first to focus on erythema in radiation-dermatitis and produces benchmark results using machine learning models. The outcome of this study validates that the proposed system can act as a pre-screening and decision support tool for oncologists or patients to provide fast, reliable, and efficient assessment of erythema grading.
Purely Organic Dyes with Thermally Activated Delayed Fluorescence—A Versatile Class of Indicators for Optical Temperature Sensing

Carbazole‐substituted dicyanobenzenes and anthraquinone based intramolecular charge‐transfer dyes, two classes of organic thermally activated delayed fluorescence (TADF) emitters developed for organic light‐emitting diode (OLED) technology, are prepared and investigated for their suitability for optical oxygen and temperature sensing. The new materials do not offer any improvement compared to the state‐of‐the‐art probes in respect to oxygen sensing. In contrast, due to very high temperature dependency of the TADF decay times, the new dyes are particularly advantageous for optical thermometry. Contrary to many state‐of‐the‐art optical thermometers, the dyes show only moderate decrease of TADF intensity at increased temperatures. The dyes immobilized into a nearly oxygen impermeable poly(vinylidene chloride‐co‐acrylonitrile) matrix feature excellent temperature sensitivity in the investigated temperature range (278–323 K) with 1.4–3.7% K−1 change of TADF lifetime at 298 K. Indicator‐loaded cell penetrating cationic nanoparticles are prepared for biological applications and feature sensitivities from 2.2 to 2.8% K−1 change of TADF lifetime at 298 K. Moreover, fiber‐optic minisensors enable fast monitoring of temperature fluctuations in small sample volumes. The outcome of our work demonstrates the high potential of organic TADF emitters for optical temperature sensing and imaging.
Faktor-Faktor Yang Memengaruhi Keputusan Pembelian Konsumen Generasi Z Di Restoran Wilayah Kelapa Gading

ABSTRAK Meningkatnya jumlah usaha makanan dan minuman serta berkembangnya teknologi dengan sangat pesat setiap tahunnya, membuat aktivitas untuk makan dan minum di luar rumah menjadi sebuah gaya hidup yang baru. Generasi Z dikenal dengan generasi yang menyukai hal yang praktis, contohnya mereka lebih memilih untuk membeli makanan dari restoran daripada menyiapkan dan memasak makanan di rumah. Oleh karena itu, penelitian ini dilakukan untuk mencari tahu tentang faktor-faktor apa saja yang memengaruhi keputusan pembelian konsumen generasi Z di restoran Kelapa Gading. Kecamatan Kelapa Gading dipilih karena daerah tersebut memiliki jumlah restoran paling banyak dibandingkan dengan kecamatan yang berada di Jakarta Utara. Data yang digunakan merupakan hasil survey dari kuisioner yang dibuat dengan skala likert. Penelitian ini merupakan penelitian kuantitatif dan menggunakan statistik inferensial untuk menganalisis hubungan variabel-variabel yang digunakan dengan keputusan pembelian konsumen generasi Z. Terdapat enam faktor yang diteliti yaitu layanan pelanggan, ketersediaan variasi dan makanan cepat saji, pemeliharaan privasi, nama merek, ketersediaan makanan siap saji, dan protokol kesehatan. Hasil yang didapatkan adalah hanya tiga faktor yang memiliki pengaruh yang signifikan terhadap keputusan pembelian generasi Z di restoran wilayah Kelapa Gading yaitu ketersediaan variasi dan makanan cepat saji, nama merek, dan ketersediaan makanan cepat saji, sedangkan tiga faktor lainnya tidak memiliki pengaruh yang banyak.Kata Kunci: statistik inferensial, generasi Z, keputusan pembelian, restoran ABSTRACTThe number of food and beverage industry and the development of its technology has grown very rapid annually, thus made the eating and drinking activities outside the homes become a new lifestyle. Generation Z is known as the generation that likes practicality, for example, they prefer to buy food from restaurants rather than preparing and cooking food at home. Consequently, this study will reveal factors that influence the purchase decisions of generation Z consumers in restaurants in Kelapa Gading district. The decision to choose Kelapa Gading district because it has the most restaurants amongst all the North Jakarta districts. The data used are the results of a survey from a questionnaire made with a Likert scale. This research is a quantitative research and uses inferential statistics to analyze the relationship between the six variables for generation Z consumers. The six variables are customer service, variety and junk food, maintenance of privacy, brand name, ready-made food, and health protocol. From the six factors studied, there are three factors that have significant influence on the purchase decisions of Generation Z at Kelapa Gading area restaurant which were availability of variety and junk food, brand name, and availability of ready-made food while the other three factors do not have much influence regarding the purchase decision.Keywords: inferential statistics, generation Z, purchase decisions, restaurants