Miracle-dz/UniFAR-FTUs huggingface dataset:
The most famous fish: human relationships with fish as inferred from the corpus of online English books (1800-2000)

Despite the historically close connection between humans and fish, the question ‘What is the most famous fish species? ’ has never been asked. I used Google Ngram viewer to estimate the frequency of times the common names of 250 fishes appear in the corpus of digitized English books published between 1800 and 2000. I propose the ‘famon’ as a unit of fame, with 1 famon = 10−6 relative % Ngram frequency. Twelve of the 250 common names are words which also have other uses in English and were thus not considered here, and 57 species had 0 famons. For the remaining 181 species, fame increased for 139 (76.8%), during or part of 1800−2000. Goldfish Carassius auratus, the most common laboratory and aquarium fish and the second fish to be domesticated, is the most famous fish, reaching 80 to 117 famons after 1930. It was introduced to Europe from China about 325 to 450 yr ago and then to North America around 1850. Goldfish have penetrated into cultural aspects of human civilization (e.g. stamps, art, music). ‘Goldfish’ also appears in the corpus of simplified Chinese, French, German, Italian, and Spanish books. The results show the universality and dominance of goldfish in the digitized published heritage. This likely indicates that non-consumptive cultural aspects, including aesthetic, spiritual, and recreational components, play a central role in defining the relationship of humans with fish, being equally important as provisioning, re gulating, and supporting services, and thus should be valued accordingly for conservation. However, cultural services have not yet been adequately integrated within the ecosystem service framework and are generally excluded from economic evaluations, a fact raising ethical issues with respect to their relative evaluation.
Aproximación a la checklist de los gipsófitos ibéricos

La estrecha relacion que existe entre determinados tipos de suelo y la flora que crece sobre ellos es conocida desde hace mucho tiempo. Los suelos de yeso son un claro exponente de este vinculo, de manera que determinadas especies vegetales crecen exclusivamente sobre ellos. Esta estrecha relacion es conocida como gipsofilia y las especies vegetales en las que es patente son las denominadas gipsofitas. La flora iberica es rica en gipsofitas, como ya puso de manifiesto Cavanilles en el siglo XVIII. Desde entonces hasta la actualidad, muchos botanicos han ido incrementando la lista de gipsofitas, pero sin que se pueda establecer un catalogo mas o menos definitivo de las mismas. Solo algunas publicaciones que se refieren a la flora de los yesos o a su vegetacion, pueden servir a modo de referencia para esbozar un primer catalogo. Esta idea ha servido como base para elaborar un listado inicial de gipsofitos sobre el que se han ido incorporando nuevas especies a partir de datos dispersos en Floras. Sobre este listado se le ha pe- dido a 12 botanicos expertos en flora gipsofila que emitieran un juicio sobre el grado de preferencia de estas especies por el yeso. Asi, se ha valorado el grado de gipsofilia de 140 especies median- te una escala del 1 al 5, de manera que este ultimo valor expresara la preferencia absoluta por el yeso. Si atendemos a los valores de la mediana, unas 50 especies pueden considerarse gipsofitos o gipsofitos preferentes.
Essential Motor Cortex Signal Processing: an ERP and functional connectivity MATLAB toolbox - User Guide

The purpose of this document is to help individuals use the "Essential Motor Cortex Signal Processing MATLAB Toolbox". The toolbox implements various methods for three major aspects of investigating human motor cortex from Neuroscience view point: (1) ERP estimation and quantification, (2) Cortical Functional Connectivity analysis and (3) EMG quantification. The toolbox -- which is distributed under the terms of the GNU GENERAL PUBLIC LICENSE as a set of MATLAB R routines -- can be downloaded directly at the address: this http URL or from the public repository on GitHub, at address below: this https URL Connectivity EMG Analysis The purpose of this toolbox is threefold: 1. Extract the event-related-potential (ERP) from preprocessed cerebral signals (i.e. EEG, MEG, etc.), identify and then quantify the event-related synchronization/desynchronization (ERS/ERD) events. Both time-course dynamics and time-frequency (TF) analyzes are included. 2. Measure, quantify and demonstrate the cortical functional connectivity (CFC) across scalp electrodes. These set of functions can also be applied to various types of cerebral signals (i.e. electric and magnetic). 3. Quantify electromyogram (EMG) recorded from active muscles during performing motor tasks.
DETERMINATION OF POROSITY BY DIELECTRIC PERMITTIVITY MEASUREMENTS IN POROUS CERAMICS

Porosity of reservoir rocks is of special interest for the oil industry. Sintered ceramics can simulate this rocks, and thereby, are a cornmon tool to study physical properties of reservoir rocks. Resistivity and permittivity measurements ha ve been used to detect fluids (water or oil) in porous rocks, however the porosity still hasn't been determined by electrical means. The effects of porosity on conductivity and on complex dielectric permittivity of porous ceramics ha ve been reported. The permitivity of a system composed of several components (labeled "mixture") can be estimated from the permittivities and concentrations of each one of the components. Using as precursor materials silica, kaolin, shale and feldspar, ceramics to simulate reservoir rocks were sintered: dense ones with poro sities less than 5% and light ones, with 2030% of porosity. These ceramics were characterized by XRD, SEM and porosity measurements. Then, conductivity and capacitance measurements were performed in order to determine the ceramic dielectric properties. The measurements were made from 10 Hz to 1 MHz at room temperature. The porosity could not be estimated from conventional "mixture laws" but, using a fractal description of the medium, it was possible to calculate the porosity of the system using a fractal description of the medium.the method was compared to Archimedes method measurements
Climate impacts on the ocean are making the Sustainable Development Goals a moving target travelling away from us

Climate change is impacting marine ecosystems and their goods and services in diverse ways, which can directly hinder our ability to achieve the Sustainable Development Goals (SDGs), set out under the 2030 Agenda for Sustainable Development. Through expert elicitation and a literature review, we find that most climate change effects have a wide variety of negative consequences across marine ecosystem services, though most studies have highlighted impacts from warming and consequences of marine species. Climate change is expected to negatively influence marine ecosystem services through global stressors—such as ocean warming and acidification—but also by amplifying local and regional stressors such as freshwater runoff and pollution load. Experts indicated that all SDGs would be overwhelmingly negatively affected by these climate impacts on marine ecosystem services, with eliminating hunger being among the most directly negatively affected SDG. Despite these challenges, the SDGs aiming to transform our consumption and production practices and develop clean energy systems are found to be least affected by marine climate impacts. These findings represent a strategic point of entry for countries to achieve sustainable development, given that these two goals are relatively robust to climate impacts and that they are important pre‐requisite for other SDGs. Our results suggest that climate change impacts on marine ecosystems are set to make the SDGs a moving target travelling away from us. Effective and urgent action towards sustainable development, including mitigating and adapting to climate impacts on marine systems are important to achieve the SDGs, but the longer this action stalls the more distant these goals will become.
Dónde está la ball? Examining the effect of code switching on bilingual children's word recognition.

Hearing words in sentences facilitates word recognition in monolingual children. Many children grow up receiving input in multiple languages - including exposure to sentences that 'mix' the languages. We explored Spanish-English bilingual toddlers' (n = 24) ability to identify familiar words in three conditions: (i) single word (ball! ); (ii) same-language sentence (Where's the ball? ); or (iii) mixed-language sentence (Dónde está la ball? ). Children successfully identified words across conditions; however, the advantage linked to hearing words in sentences was present only in the same-language condition. This work hence suggests that language mixing plays an important role on bilingual children's ability to recognize spoken words.
Autonomous valve operation by a manipulator using a monocular camera and a single shot multibox detector

Manipulators on rescue robots must open doors and valves and move debris that impedes movement. We constructed a manipulator equipped with a monocular camera. If a manipulator could perform the above operations autonomously, disaster victims could be found more rapidly. Stereo cameras are often used to determine object positions. A manipulator requires a stereo camera to see gaps between rubble. However, stereo cameras are larger, heavier, and more complex than monocular cameras. It would be very useful if a monocular camera could determine the position of an object. The manipulator could probe narrower gaps in dim light and reduce the motor load. Doorknobs and valves that must be opened in a disaster environment are often standardized. If the object size is fixed, we considered it possible to identify the object and to measure its position and distance using a single-eye camera. We focused specifically on valve operation. Our manipulator can be mounted on a rescue robot. The control system features inverse kinematics. The manipulator end effector is moved to the target coordinates. A simulator displays manipulator position and orientation in real time. Our manipulator detected and rotated valves autonomously.
Image Registration Method from LDCT Image Using FFD Algorithm

In recent years, the number of lung cancer deaths has been increasing. In Japan, CT (Computed Tomography) equipment is used for its visual screening. However, there is a problem that seeing huge number of images taken by CT is a burden on the doctor. To overcome this problem, the CAD (Computer Aided Diagnosis) system is introduced on medical fields. In CT screening, LDCT (Low Dose Computed Tomography) screening is desirable considering radiation exposure. However, the image quality which is caused the lower the dose is another problem on the screening. A CAD system that enables accurate diagnosis even at low doses is needed. Therefore, in this paper, we propose a registration method for generating temporal subtraction images that can be applied to low-quality chest LDCT images. Our approach consists of two major components. Firstly, global matching based on the center of gravity is performed on the preprocessed images, and the region of interest (ROI) is set. Secondly, local matching by free-form deformation (FFD) based on B-Spline is performed on the ROI as final registration. In this paper, we apply our proposed method to LDCT images of 6 cases, and reduce 57.29% in the calculation time, 26.1% in the half value width, and 29.6% in the sum of histogram of temporal subtraction images comparing with the conventional method.
Muslim- Students‟ Psychological Adjustment in MANUU-Girls‟ Hostel: A Survey

Article History Published Online: 14 Oct 2019 Education is the weapon that changes a person-life. Psychological adjustment is necessary for students to study satisfactorily and happily but boarders of hostels live in a different environment in which they have never lived before, so they may have psychological adjustment problem that is like a virus eating their peace of mind. Qiang Wang and Qian Zhang state about psychological maladjustment harm “If someone had serious adjustment problems when entering in college, he or she might do extreme things on campus (e.g., suicide, aggression, inferiority, autism). Thus, problems of adjustment will do harm to students' quality of daily life and mental health. ”
Nuclear-translocated Glyceraldehyde-3-phosphate Dehydrogenase Promotes Poly(ADP-ribose) Polymerase-1 Activation during Oxidative/Nitrosative Stress in Stroke*

Background: The link between poly(ADP-ribose) polymerase-1 (PARP-1) and nuclear-translocated glyceradehyde-3-phosphate dehydrogenase (GAPDH) in neurons under oxidative/nitrosative stress remains unknown. Results: The N terminus of nuclear GAPDH binds with PARP-1, and this complex promotes PARP-1 overactivation both in vitro and in vivo. Conclusion: Nuclear GAPDH is a key PARP-1 regulator. Significance: GAPDH/PARP-1 signaling underlies oxidative/nitrosative stress-induced brain damage such as stroke. In addition to its role in DNA repair, nuclear poly(ADP-ribose) polymerase-1 (PARP-1) mediates brain damage when it is over-activated by oxidative/nitrosative stress. Nonetheless, it remains unclear how PARP-1 is activated in neuropathological contexts. Here we report that PARP-1 interacts with a pool of glyceradehyde-3-phosphate dehydrogenase (GAPDH) that translocates into the nucleus under oxidative/nitrosative stress both in vitro and in vivo. A well conserved amino acid at the N terminus of GAPDH determines its protein binding with PARP-1. Wild-type (WT) but not mutant GAPDH, that lacks the ability to bind PARP-1, can promote PARP-1 activation. Importantly, disrupting this interaction significantly diminishes PARP-1 overactivation and protects against both brain damage and neurological deficits induced by middle cerebral artery occlusion/reperfusion in a rat stroke model. Together, these findings suggest that nuclear GAPDH is a key regulator of PARP-1 activity, and its signaling underlies the pathology of oxidative/nitrosative stress-induced brain damage including stroke.
Evolutionary distinctiveness of the extinct Yunnan box turtle (Cuora yunnanensis) revealed by DNA from an old museum specimen

Cuora yunnanensis is an extinct turtle known from 12 specimens collected from Yunnan, China, before 1908. We used ancient DNA methods to sequence 1723 base pairs of mitochondrial DNA from a museum specimen of C. yunnanensis. Unlike some rare ‘species’ recently described from the pet trade, C. yunnanensis represents a lineage that is distinct from other known turtles. Besides C. yunnanensis, two other valid species (C. mccordi, C. zhoui) are unknown in the wild but are supposedly from Yunnan. Intensive field surveys for surviving wild populations of these critically endangered species are urgently needed.
psi Polarization in pp Collisions at root s = 7 TeV

Abelev, B. ; Quintana, A. Abrahantes; Adamova, D. ; Adare, A. M. ; Aggarwal, M. M. ; Rinella, G. Aglieri; Agocs, A. G. ; Agostinelli, A. ; Aguilar Salazar, S. ; Ahammed, Z. ; Ahmad, N. ; Masoodi, A. Ahmad; Ahn, S. U. ; Akindinov, A. ; Aleksandrov, D. ; Alessandro, B. ; AlfaroMolina, R. ; Alici, A. ; Alkin, A. ; Almaraz Avina, E. ; Alt, T. ; Altini, V. ; Altinpinar, S. ; Altsybeev, I. ; Andrei, C. ; Andronic, A. ; Anguelov, V. ; Anson, C. ; Anticic, T. ; Antinori, F. ; Antonioli, P.; Aphecetche, L. ; Appelshaeuser, H. ; Arbor, N. ; Arcelli, S. ; Arend, A. ; Armesto, N. ; Arnaldi, R. ; Aronsson, T. ; Arsene, I. C. ; Arslandok, M. ; Asryan, A. ; Augustinus, A. ; Averbeck, R. ; Awes, T. C. ; Aysto, J.; Azmi, M. D. ; Bach, M. ; Badala, A. ; Baek, Y. W.
A sub-exponential branching process to study early epidemic dynamics with application to Ebola

Exponential growth is a mathematically convenient model for the early stages of an outbreak of an infectious disease. However, for many pathogens (such as Ebola virus) the initial rate of transmission may be sub-exponential, even before transmission is affected by depletion of susceptible individuals. We present a stochastic multi-scale model capable of representing sub-exponential transmission: an in-homogeneous branching process extending the generalised growth model. To validate the model, we fit it to data from the Ebola epidemic in West Africa (2014–2016). We demonstrate how a branching process can be fit to both time series of confirmed cases and chains of infection derived from contact tracing. Our estimates of the parameters suggest transmission of Ebola virus was sub-exponential during this epidemic. Both the time series data and the chains of infections lead to consistent parameter estimates. Differences in the data sets meant consistent estimates were not a foregone conclusion. Finally, we use a simulation study to investigate the properties of our methodology. In particular, we examine the extent to which the estimates obtained from time series data and those obtained from chains of infection data agree. Our method, based on a simple branching process, is well suited to real-time analysis of data collected during contact tracing. Identifying the characteristic early growth dynamics (exponential or sub-exponential), including an estimate of uncertainty, during the first phase of an epidemic should prove a useful tool for preliminary outbreak investigations. Author Summary Epidemic forecasts have the potential to support public health decision making in outbreak scenarios for diseases such as Ebola and influenza. In particular, reliable predictions of future incidence data may guide surveillance and intervention responses. Existing methods for producing forecasts, based upon mechanistic transmission models, often make an implicit assumption that growth is exponential, at least while susceptible depletion remains negligible. However, empirical studies suggest that many infectious disease outbreaks display sub-exponential growth early in the epidemic. Here we introduce a mechanistic model of early epidemic growth that allows for sub-exponential growth in incidence. We demonstrate how the model can be applied to the types of data that are typically available in (near) real-time, including time series data on incidence as well as individual-level case series and chains of transmission data. We apply our methods to publically available data from the 2014–2016 West Africa Ebola epidemic and demonstrate that early epidemic growth was sub-exponential. We also investigate the statistical properties of our model through a simulation re-estimation study to identify it performance characteristics and avenues for further methodological research.
Stagioni: Temperature management to enable near-sensor processing for energy-efficient high-fidelity imaging.

Vision processing on traditional architectures is inefficient due to energy-expensive off-chip data movement. Many researchers advocate pushing processing close to the sensor to substantially reduce data movement. However, continuous near-sensor processing raises the sensor temperature, impairing the fidelity of imaging/vision tasks. We characterize the thermal implications of using 3D stacked image sensors with near-sensor vision processing units. Our characterization reveals that near-sensor processing reduces system power but degrades image quality. For reasonable image fidelity, the sensor temperature needs to stay below a threshold, situationally determined by application needs. Fortunately, our characterization also identifies opportunities -- unique to the needs of near-sensor processing -- to regulate temperature based on dynamic visual task requirements and rapidly increase capture quality on demand. Based on our characterization, we propose and investigate two thermal management strategies -- stop-capture-go and seasonal migration -- for imaging-aware thermal management. We present parameters that govern the policy decisions and explore the trade-offs between system power and policy overhead. Our evaluation shows that our novel dynamic thermal management strategies can unlock the energy-efficiency potential of near-sensor processing. For our evaluated tasks, our strategies save up to 53% of system power with negligible performance impact and sustained image fidelity.
Force Control for Soft Robotic Hands Applied to Grasping

Tran Nguyen Le: Force Control for Soft Robotic Hands Applied to Grasping Master’s thesis Tampere University Master of Science (Technology) Factory Automation and Industrial Informatics August 2019 Robotic grasping has been studied for more than 30 years, but it is still a challenging field. Today, most robotic grippers are rigid, making it hard for them to grasp and handle irregularly shaped objects that are delicate and easily deformed such as a compact disc, an egg, or an empty plastic cup. To tackle this issue, soft robotic hands have been introduced. Despite advantages of soft robotic hands, their applications are still limited to simple pick-and-place tasks. The main reason for this is their lack of sensing capabilities, which leads to the absence of information about the internal state of the hand or the interaction between the hand and the environment. This thesis aims to tackle this issue by integrating appropriate sensors into a soft robotic hand. The information extracted from the sensory readings is then used to develop a control strategy to study the interaction between the hand and objects. Experiments performed on the developed soft hand and controller board showed that the interaction between the hand and objects could be studied by using only sensors integrated into the hand. The final results also showed that this information could be used to successfully control the soft hand in real time to achieve a manipulation task such as grasping deformable planar objects especially thin-shell objects like empty plastic cups.
Minimization of Classifier Construction Cost for Search Queries

Search over massive sets of items is the cornerstone of many modern applications. Users express a set of properties and expect the system to retrieve qualifying items. A common difficulty, however, is that the information on whether an item satisfies the search criteria is not explicitly recorded in the repository. Instead, it may be general knowledge or "hidden" in a picture/description, leading to incomplete search results. To overcome this problem, companies build dedicated classifiers that determine which items satisfy the given criteria. However, building classifiers requires volumes of high-quality labeled training data. Since the costs of training classifiers for different subsets of properties can vastly differ, the choice of which classifiers to train has great monetary significance. The goal of our research is to devise effective algorithms to choose which classifiers one should train to address a given query load while minimizing the cost. Previous work considered a simplified model with uniform classifier costs, and queries with two properties. We remove these restrictions in our model. We prove NP-hard inapproximability bounds and devise several algorithms with approximation guarantees. Moreover, we identify a common special case for which we provide an exact algorithm. Our experiments, performed over real-life datasets, demonstrate the effectiveness and efficiency of our algorithms.