Miracle-dz/UniFAR-FTUs huggingface dataset:
Description of a New Cobra (Naja Laurenti, 1768; Squamata, Elapidae) from China with Designation of a Neotype for Naja atra

Simple Summary Cobras (Naja Laurenti, 1768) are a group of well-known highly venomous snakes, which cause numerous cases of snakebites every year, especially in South Asia and Southern China. Taxonomic framework is essential for the medical treatment of snake bites and accurate antivenin development. However, the taxonomy of Asian cobras is still puzzling, especially for the widespread species Monocled Cobra (N. kaouthia Lesson, 1831). This study provided new materials and understanding for the taxonomy of this species by combining mitochondrial phylogenetic analysis and morphological comparisons based on samples from a vast area in Asia. The results showed that the Chinese population of N. kaouthia represents a new species. This study also provided new data for N. atra and designated a neotype for it. Furthermore, the subspecies N. naja polyocellata was resurrected and recognized as a full species, N. polyocellata comb. nov., and the subspecies N. sumatrana miolepis was also resurrected. This study highlighted the necessity to evaluate the effectiveness of cobra antivenin based on a comprehensive taxonomic framework. Abstract Taxonomic frameworks for medically important species such as cobras (genus Naja Laurenti, 1768; Squamata, Elapidae) are essential for the medical treatment of snake bites and accurate antivenin development. In this paper, we described the former N. kaouthia populations recorded from China as a new species and designated a neotype for N. atra-based morphological and mitochondrial phylogenetic analysis. The new species N. fuxi sp. nov. was morphologically diagnosed from N. kaouthia by (1) regular single narrow crossband present on the middle and posterior parts of the dorsum (3–15, 7.9 ± 2.7, n = 32) and the dorsal surface of the tail (1–6, 4.2 ± 1.1, n = 32) of both adults and juveniles, buff-colored with dark fringes on both edges, vs. South Asian populations (n = 39) and Southeast Asian populations (n = 35) without cross bands, with irregular cross bands or multiple light-colored crossbands pairs, or densely woven lines; (2) small scales between the posterior chin shields, usually three (40%) or two (37%), rarely four (13%), or one (10%) (n = 30) vs. mostly one (81%) and rarely two (19%) (n = 28); (3) ventrals 179–205 (195.4 ± 6.7, n = 33) vs. South Asian populations 179–199 (188.7 ± 5.9, n = 12); Southeast Asian populations 168–186 (177.8 ± 4.9, n = 18). Phylogenetically, the new species forms an independent sister clade to the clade including N. atra, N. kaouthia, N. oxiana and N. sagittifera. Furthermore, the subspecies N. naja polyocellata should be resurrected and recognized as a full species, N. polyocellata comb. nov., and the subspecies N. sumatrana miolepis should be resurrected.
Understanding the Translocation Dynamics of Nile Tilapia (Oreochromis niloticus) and Its Ecological Consequences in East Africa

The Nile tilapia (Oreochromis niloticus) is the second-most economically important fish species in East African countries (EAC), surpassed only by the Nile perch (Lates niloticus). It is the most-farmed freshwater fish species in EAC and the second-most-farmed worldwide. Currently, in EAC, through direct stocking activities and likely indirectly via aquaculture escapees, Nile tilapia are present in waterbodies where it is not native and where it is thought to have contributed to the fish biodiversity loss observed in recent decades. Introduced Nile tilapia may hybridise with native, congeneric species, promoting genetic introgression that can be detrimental to the sustainability of biodiversity. Moreover, the translocation dynamics and escapes from aquaculture can contribute to artificial geneflow between Nile tilapia stocks, compromising their gene pool and the sustainability of the species as a fishery resource. In the current work, we review some examples of these phenomena in EAC. Additionally, we explore the importance of collecting genetic data to define baseline knowledge for native and non-native Nile tilapia populations that can be used in monitoring programmes for development, management and conservation of tilapia genetic resources.
The Potential Protective Role of Neoeriocitrin in a Streptozotocin-Induced Diabetic Model in INS-1E Pancreatic ß-Cells

: Diabetes mellitus is a very common metabolic disorder. In addition to the use of drugs, plant-based antidiabetic products are also used as an alternative therapy. Although the main cause of the β-cell damage is not known exactly, it is attributed to oxidative stress. Although antioxidant effects of flavonoids are well known, there is an information gap about neoeriocitrin (Neo). Neo is found in fruit extracts, fruit juices of some plants. In this study, the potential protective effect of pretreatment of Neo was examined in pancreatic INS-1E cells against STZ-induced damage. INS-1E cells were pre-treated with Neo (0.25, 0.5, 1 µM) for 21 hours, and diabetes was induced by STZ. The
The multi-wavelength quasar survey - IV. Quasars in the Leo cluster

We aim to provide a quasar sample that is more complete than any previous surveys by using a combined selection technique to reduce the selection effects. Here we present the observational results for the X-ray candidates in the field of the Leo Cluster. We found 33 X-ray AGNs in this field of which 10 are new discoveries. The X-ray data and optical spectra of these AGNs are given. We also study the near-IR properties of the X-ray-selected AGNs by using the data from 2MASS. Most of the AGNs in our sample span the color range 0.0 < B − J < 2.5, 1.0 < J − K s < 2.0 and 0.5 < H − K s < 1.2.
THE GAME – MARGINALISERING OG KOMPLEKSE KONSTITUERINGER AF OVERSKRIDENDE FORANDRINGSBEVÆGELSER

Hvordan går det til, at Mounir, der ad flere omgange har været udsluset til specialtilbud og har hængt på gaden i fællesskaber, hvor det at hærge biler og lave hærværk var noget, der gav credit, i dag er i gang med at færdiggøre 3. g som en af de bedste i sin klasse? Er det Mounir, der er gjort af et særligt mønsterbryder-“stof”? Skyldes det hans forældre, der altid har opmuntret og støttet Mounir til at tage en uddannelse? Er det på grund af måden, Mounir klæder sig på? Eller er det snarere på grund af forskellige støttende lærere, både i folkeskolen og i specialtilbuddene dengang i 1. -2. og igen i 6. -7. klasse? Indeværende artikel foreslår med Mounirs egen metafor om gamet, hvordan dette game kan forstås som et sammensurium af mange forskellige kræfter. Analyserne peger på nogle af de kræfter, der blander sig og væver sig ind i hinanden, og på hvordan disse kan forstås som medproducerende for Mounirs særlige og forandrende tilblivelsesprocesser.
Real‐life research projects improve student engagement and provide reliable data for academics

Abstract Student engagement can have a positive influence on student success. Many methods exist for fostering engagement but tend to be generic and require tailoring to specific contexts, subjects, and students. In the case of undergraduate science students, practical classes are a popular tool for increasing engagement. However, despite strong potential for improvement via links with “real life” research projects (RLRPs), few academic staff incorporate research participation with teaching activities. This is potentially due to poor time availability and low opinions of students' ability to collect reliable data. This study aims to examine whether involvement with RLRPs can generate reliable scientific data and also act as a motivational tool for engaging tertiary science students. A preexisting core activity for first‐year biology and marine biology students was modified to include a short RLRP component. Student‐based data collection and a questionnaire about experiences were used to examine the reliability of student‐collected data and student perceptions of RLRPs. Results indicated that error rate in student‐collected data was minimal. Irrespective of participating in a “normal” practical class or a class with a RLRP component, students collected equally accurate data. However, when the topic aligned specifically with their degree subject, student accuracy was higher. All students surveyed reported high motivation with the idea of RLRP participation, placing high importance on this from an educational and employability perspective. Yet, students were not confident about participating in RLRPs until they had engaged with one, suggesting that introducing such projects into taught sessions early‐on may encourage students to seek further opportunities in the future. In conclusion, incorporating RLRPs into the curriculum of undergraduate science courses has considerable potential benefits for both students and academic staff.
Comparison of the Effects of Trained and Untrained Futsal on Vital Signs

— Futsal is a high-intensity sport that can affect changes in vital signs. The research aimed to find out the comparison of futsal effects on trained and untrained vital signs. There are five variables in this research: Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Body Temperature (T), Pulse Frequency (PF), and Respiratory Rate (RR). This research used a pre-experimental pretest-posttest design method with the training of futsal sports 2 x 20 minutes in 3 weeks. The location of the experiment was Litha Indoor Soccer Makassar. The number of samples was 20 respondents aged 18-25 years old, selected by purposive sampling. Data were analyzed by the Paired-Samples T-Test and Wilcoxon test with a significance level of p <0.05. The statistical analysis showed that the futsal affects the SBP, DBP, PF and RR of the trained group. In contrast, there is a significant influence of futsal on diastolic blood pressure, body temperature, and pulse frequency in the untrained group. The research concluded that there were no significant effects of vital signs on the trained group. At the same time, there were significant effects of crucial signs on the untrained group. Otherwise, there was no significant effect on SBP and RR. It means there is a comparison of futsal effects on trained and untrained vital signs in young adults. The changes in vital signs for unskilled are greater than for trained.
Effect of the illumination method on photo-acoustic image quality with array transducer based system

Photo-acoustic imaging (PAI) is a hybrid imaging modality, which can offer a high contrast tomographic image with ultrasound like resolution in depth of centimeters. Additionally, it has been studied well as functional imaging modality using characteristics that can distinguish by absorption spectra. Our purpose is to investigate the image quality and potential of photo-acoustic (PA) image as a preliminary study toward the medical diagnosis applications. For this purpose, firstly we focused on the difference of image quality between photo-acoustic image and ultrasound image using array transducers system. Secondly we examined the effect of illumination method on photo-acoustic image quality. We compared both photo-acoustic image and ultrasound image of a phantom using original PAI experimental apparatus system with 192ch PZT array probe. Resolution of PAI and ultrasound image could be revealed, based on the optimized reconstruction method for each using each element data. We demonstrated higher resolution and higher contrast of photo-acoustic image than ultrasound image. To examine the effect on photo-acoustic image quality, we analyzed depth-dependent signal attenuation in scattering media under various illumination methods such as the expansion of illumination area. Our analysis with experiments and Monte Carlo simulation are performed to show the necessity for illumination optimization depend on the application and probe size.
Distributed detection of communities in complex networks using synthetic coordinates

Various applications like finding Web communities, detecting the structure of social networks, and even analyzing a graph’s structure to uncover Internet attacks are just some of the applications for which community detection is important. In this paper, we propose an algorithm that finds the entire community structure of a network, on the basis of local interactions between neighboring nodes and an unsupervised distributed hierarchical clustering algorithm. The novelty of the proposed approach, named SCCD (standing for synthetic coordinate community detection), lies in the fact that the algorithm is based on the use of Vivaldi synthetic network coordinates computed by a distributed algorithm. The current paper not only presents an efficient distributed community finding algorithm, but also demonstrates that synthetic network coordinates could be used to derive efficient solutions to a variety of problems. Experimental results and comparisons with other methods from the literature are presented for a variety of benchmark graphs with known community structure, derived from varying a number of graph parameters and real data set graphs. The experimental results and comparisons to existing methods with similar computation cost on real and synthetic data sets demonstrate the high performance and robustness of the proposed scheme.
Measurement of Polarizability of Cesium nD State in Magneto-Optical Trap

The Stark spectrum of cesium n D ( n = 39–50) Rydberg atoms are obtained by a state-selective field ionization method in a magneto-optical trap (MOT). The Stark shifts of Rydberg atoms are measured experimentally, the scalar and tensor polarizabilities of Rydberg atoms are obtained by fitting the experimental data, and the results are found to be in agreement with the existing theoretical calculations.
Problems, Management, and Prospects of Acid Sulphate Soils in the Ganges Delta

Soil is a finite natural resource and is indispensable for human civilization because it is the medium for food production for the biosphere. Continued soil degradation is a forerunner of catastrophe for the living world. The protection of healthy soils and the restoration of problem soils are strongly needed in the current agricultural scenario as competition for urbanization and other human needs for land resources limits the scope for the further availability of land for agriculture. Naturally occurring degraded soils, such as acid sulphate soils, can be restored with scientific interventions and advanced management strategies. The Ganges Delta is a densely populated region, where the inhabitants’ major livelihood is agriculture. Soil acidity and salinity restrict crop performance in this coastal region, particularly the acid sulphate soils (ASSs) posing a risk to agriculture. ASSs are developed from land-use changes from mangrove forest to agricultural land in this region. There is no systematic study on these soil types covering Bangladesh and India. This paper unfolds several aspects related to the characteristics, problems, and detailed management strategies of ASSs relevant to the Gangetic Delta region where these soils continue to be used for intensive agriculture to meet the livelihood needs. Crop yields are very poor in the unmanaged ASSs due to a very low soil pH (<3.5), hampering the growth and development of crops due to nutrient deficiencies and/or toxicities, coupled with soil salinity. There is toxicity of water-soluble Fe, Al, and Mn. The phosphorus nutrition of crops in these soils is affected owing to a high soil P fixation capacity. A deficiency of micronutrients, such as Zn and Cu, was also observed; however, K availability is variable in the soil. The soil acidity is a general problem throughout the soil profile; however, extreme acidity (pH < 3.5) in particular soil horizons is a typical soil characteristic, which creates problems for its efficient management. Specific operations, such as the selective use of soil layers with good properties for crop root growth, major and minor nutrient applications, and soil amendments, including green manuring, application of biofertilizers, and soil microbes, are gradually improving the properties of these soils and bringing back the potential for good crop production. Scientific water/drainage management is needed to gain an agronomic advantage. Evidence of increased crop yields in these soils observed from green manuring, lime, basic slag, and rock phosphate application are presented.
Locating of macro-inhomogeneity in random turbid medium by using artificial neural networks

Nowadays the artificial neural network (ANN), an effective powerful technique that is able denoting complex input and output relationships, is widely used in different biomedical applications. In present Letter the applying of ANN for the determination of characteristics of random highly scattering medium (like bio-tissue) is considered. Spatial distribution of the back-scattered light calculated by Monte Carlo method is used to train ANN for single and multiply scattering regimes. The potential opportunities of use of ANN for image reconstruction of an absorbing macro inhomogeneity located in topical layers of random scattering medium are presented. This is especially of high priority because of new diagnostics/treatment developing that is based on the applying gold nano-particles for labeling cancer cells.
Mechanism for Major Disruptions in Tokamaks

A mechanism is proposed for the major disruption in tokamaks that involves the nonlinear destabilization of odd m tearing modes by the m = 2/n = 1 tearing mode, where m and n denote the poloidal and toroidal mode numbers, respectively. The magnetic islands generated can extend across the plasma cross section. For resistivities of the order of magnitude of those in TOSCA and LT-3, the time scale for their appearance is consistent with the time for the major disruption.
Interaction between Movement Proteins of Hibiscus green spot virus

Movement proteins (MPs) of plant viruses enable the translocation of viral genomes from infected to healthy cells through plasmodesmata (PD). The MPs functions involve the increase of the PD permeability and routing of viral genome both to the PD entrance and through the modified PD. Hibiscus green spot virus encodes two MPs, termed BMB1 and BMB2, which act in concert to accomplish virus cell-to-cell transport. BMB1, representing an NTPase/helicase domain-containing RNA-binding protein, localizes to the cytoplasm and the nucleoplasm. BMB2 is a small hydrophobic protein that interacts with the endoplasmic reticulum (ER) membranes and induces local constrictions of the ER tubules. In plant cells, BMB2 localizes to PD-associated membrane bodies (PAMBs) consisting of modified ER tubules and directs BMB1 to PAMBs. Here, we demonstrate that BMB1 and BMB2 interact in vitro and in vivo, and that their specific interaction is essential for BMB2-directed targeting of BMB1 to PAMBs. Using mutagenesis, we show that the interaction involves the C-terminal BMB1 region and the N-terminal region of BMB2.
Breakdown of the slow manifold in the Shallow-Water equations

Abstract Numerical solutions are obtained by implicit multigrid solvers for initial-value problems in the rotating Shallow-Water Equations (SWE) with spatially complex initial conditions. Companion solutions are also obtained with the Shallow-Water Balance Equations (SWBE), both to determine the initial conditions for the SWE and to provide a comparison solution that lies entirely on the slow, advective manifold. We make use of a control parameter (here the Rossby number, R) to regulate the degree of slowness and balance. While there are measurable discrepancies between the evolving SWE and SWBE solutions for all R, there is a distinct, spatially local breakdown both of the slow manifold in the SWE solution and in the closeness of correspondence between the SWE and SWBE solutions. This critical value for breakdown is only slightly smaller than the R values at which, first, the SWE evolution becomes singular (i.e., the fluid depth vanishes), or second, a consistent initial condition for the SWBE cannot be .
Machine-component grouping in cellular manufacturing by multidimensional scaling

Abstract A heuristic is proposed for grouping of machines and components in cellular manufacturing. The method adopts the principle of strength coefficient using multidimensional scaling. The method has been found to give efficient solutions while taking less computational time. The algorithm is tested against five existing test problems taken from the literatures and is further compared with the two most commonly cited algorithms, i.e. rank order clusturing (ROC) and close neighbour algorithm (CNA).
MODELING AND SIMULATION OF NEAR-EARTH WAVE PROPA- GATION IN PRESENCE OF A TRUNCATED VEGETATION LAYER

liao1051 Date Received: September 14, 2005 1. (a) DaHan Liao 1301 Beal Avenue EECS Building Room 3124 Ann Arbor, MI 48109 U.S.A. liaod@umich.edu (b) 734-763-4185 (c) 2. F Wave Propagation and Remote Sensing
Implimentasi Geometri BIM-GIS Terhadap Navigasi Pengguna bagi Persekitaran Dalaman: Satu Kajian

The integration between Building Information Modeling (BIM) and Geographic Information System (GIS) is frequently discussed from time to time due to the benefits offered, especially for user navigation in the building’s indoor environment. Inequality in terms of 3D geometry and level of detail was identified as contributing to the difficulty in integrating the two models. Although there are limitations, various studies have been conducted to improve the method of integration so that the data can be utilised successfully. Therefore, this paper focuses on reviewing relevant research papers to (1) identify the basic information and structure of BIM and GIS models, (2) study the relationship and integration that occurs between the two types of models at the model geometry level, and (3) identify the application of the user navigation to the indoor building environment and highlight the future direction for the integration of BIM and GIS study. From this study, it can be identified that the standardised geometry schemes are the keys to the success of BIM and GIS integration. It can indirectly enhance the interoperability of data and helps in the development of a holistic data model for a broader scope of application. Particularly in the era of rapid development of machine learning, deep learning and internet of things (IoT) technology, where the application of integrated products through semantic web methods is seen to have an expansive room to grow significantly for location-based services (LBS) and emergency application.
Tensor response quantile regression with neuroimaging data

Collecting neuroimaging data in the form of tensors (i.e. multidimensional arrays) has become more common in mental health studies, driven by an increasing interest in studying the associations between neuroimaging phenotypes and clinical disease manifestation. Motivated by a neuroimaging study of post‐traumatic stress disorder (PTSD) from the Grady Trauma Project, we study a tensor response quantile regression framework, which enables novel analyses that confer a detailed view of the potentially heterogeneous association between a neuroimaging phenotype and relevant clinical predictors. We adopt a sensible low‐rank structure to represent the association of interest, and propose a simple two‐step estimation procedure which is easy to implement with existing software. We provide rigorous theoretical justifications for the intuitive two‐step procedure. Simulation studies demonstrate good performance of the proposed method with realistic sample sizes in neuroimaging studies. We conduct the proposed tensor response quantile regression analysis of the motivating PTSD study to investigate the association between fMRI resting‐state functional connectivity and PTSD symptom severity. Our results uncover non‐homogeneous effects of PTSD symptoms on brain functional connectivity, which cannot be captured by existing tensor response methods.