Miracle-dz/UniFAR-FTUs huggingface dataset:
HEAT LOAD PREDICTION IN DISTRICT HEATING AND COOLING SYSTEMS THROUGH A RECURRENT NEURAL NETWORK WITH DATA CHARACTERISTICS

Heat load prediction in district heating and cooling (DHC) systems is one of the key technologies for economical and safe operations of DHC systems. The heat load prediction method using a three-layered neural network proposed by the authors has been used in an actual DHC plant on a trial basis. However, there exists a drawback that its prediction becomes less accurate in periods when the heat load is nonstationary. In this paper, we improve the heat load prediction method through the introduction of a recurrent neural network for adapting the dynamical variation of heat load together with a new kind of input data in consideration of the characteristics of heat load data. In order to show the eﬃciency of the proposed method, we carry out several numerical experiments using actual heat load data.
The rostral ventrolateral medulla mediates the sympathoactivation produced by chemical stimulation of the rat nasal mucosa

1 We sought to outline the brainstem circuit responsible for the increase in sympathetic tone caused by chemical stimulation of the nasal passages with ammonia vapour. Experiments were performed in α‐chloralose‐anaesthetized, paralysed and artificially ventilated rats. 2 Stimulation of the nasal mucosa increased splanchnic sympathetic nerve discharge (SND), elevated arterial blood pressure (ABP), raised heart rate slightly and inhibited phrenic nerve discharge. 3 Bilateral injections of the broad‐spectrum excitatory amino acid receptor antagonist kynurenate (Kyn) into the rostral part of the ventrolateral medulla (RVLM; rostral C1 area) greatly reduced the effects of nasal mucosa stimulation on SND (‐80 %). These injections had no effect on resting ABP, resting SND or the sympathetic baroreflex. 4 Bilateral injections of Kyn into the ventrolateral medulla at the level of the obex (caudal C1 area) or into the nucleus tractus solitarii (NTS) greatly attenuated the baroreflex and significantly increased the baseline levels of both SND and ABP. However they did not reduce the effect of nasal mucosa stimulation on SND. 5 Single‐unit recordings were made from 39 putative sympathoexcitatory neurons within the rostral C1 area. Most neurons (24 of 39) were activated by nasal mucosa stimulation (+65·8 % rise in discharge rate). Responding neurons had a wide range of conduction velocities and included slow‐conducting neurons identified previously as C1 cells. The remaining putative sympathoexcitatory neurons were either unaffected (n= 8 neurons) or inhibited (n= 7) during nasal stimulation. We also recorded from ten respiratory‐related neurons, all of which were silenced by nasal stimulation. 6 In conclusion, the sympathoexcitatory response to nasal stimulation is largely due to activation of bulbospinal presympathetic neurons within the RVLM. We suggest that these neurons receive convergent and directionally opposite polysynaptic inputs from arterial baroreceptors and trigeminal afferents. These inputs are integrated within the rostral C1 area as opposed to the NTS or the caudal C1 area.
Acute myelofibrosis terminating in an acute lymphoblastic leukemia. A case report

A patient with acute myelofibrosis developed acute leukemia during the course of her disease. Light microscopic examination showed that the cells were lymphoblasts. The presence of terminal deoxynucleotidyl transferase and T‐and B‐lymphocyte markers suggested that the malignancy was of immature lymphoid cell origin. Terminal leukemic transformation in some cases of acute myelofibrosis may be of a lymphoid nature and, thus, less toxic chemotherapy could be used with a better prognosis. Cancer 46:615–618, 1980.
An Efficient Lip-reading Method Using K-nearest Neighbor Algorithm

Many studies have been carried out on lip reading, most of those works are based on color images, while some essential features might not be obtained, like inner lip information. In this paper, RGB-D camera will be introduced for improving the recognition rate of lip reading. We try to complete lip reading through using only gray-scale images. Thirteen groups of words are given, and we present eight features for classification. Volunteers are asked to sit in the front of RGB-D camera. For each word we select 15 frames. K-nearest neighbor algorithm (KNN) is used to select the same words between different volunteers. DOI: http://dx.doi. org/10.11591/telkomnika.v13i1. 6872
A Noninvasive and Speculative Method of Visualizing Latent Fingerprint Deposits on Thermal Paper

Latent fingerprint deposits on thermal paper have been visualized noninvasively at visible wavelengths when illuminated with a UV‐A light source (peak 365 nm). A higher intensity UV source (250 W/m2 at 0.38 m) gave superior fingerprint visibility when compared with a 60 W/m2 (at 0.4 m) source. Removing the visible (blue) component of the light source emission did not adversely affect the visibility of the fingerprint. Sample fingerprints from 100 donors, when examined 24 h after deposition, produced identifiable fingerprints from nearly 34% of fingerprint deposits. A mechanism for the observed visibility is proposed based on low emission of visible wavelengths from areas of thermal paper coincident with the fingerprint deposit, when illuminated with UV. This is likely due to a weak color change in the thermal paper dye arising from protonated amino acid components of the sweat. This effect was not observed on nonthermal paper.
Selective harmonic elimination: An comparative analysis for seven level inverter

Various control and modulation techniques such as Sine Pulse Width Modulation (SPWM), Space Vector modulation (SVM) and Selective Harmonic Elimination (SHE) have been used for multilevel inverter (MLI). The best method is SHE due to low switching losses and it suppress the specific unwanted harmonic. The various algorithms such as Genetic Algorithm (GA), bee algorithm, resultant theory and swarm intelligence have been applied by researchers. In this paper, a comparative analysis of SHE based seven levels inverter have been made using Particle Swarm Optimization (PSO), Simulated Annealing (SA), Bat Algorithm (BA) and Cuckoo Search Algorithm (CSA). The simulation has been done by MATLAB for seven level and the performance has been verified experimentally.
A new species of Rana from the Dabie Mountains in eastern China (Anura, Ranidae)

Abstract A new species Rana dabieshanensis sp. n. is described from the Dabie Mountains in Anhui Province, China, based on morphological character differences and molecular analyses. The new species can be distinguished from its congeners by a combination of diagnostic characters. The results of phylogenetic analyses (based on 12s rRNA, 16s rRNA, ND2, Cyt b, RAG1, BDNF and Tyr) and genetic distances (based on Cyt b) indicate that the new species belongs to the Rana longicrus group, and is placed as the sister taxon to R. hanluica.
The Relationship of Self-Esteem, Impulsivity and Temperament in Bipolar Patients: Is it Differentially Related to Gender?

Objective: The aim of this study was to investigate the relation between self-esteem, impulsivity and temperament, and to investigate whether it is differentially related to gender. Methods: One hundred consecutive cases who referred to our outpatient clinic for routine control and gave informed consent and who were diagnosed with Bipolar Disorder according to DSM-IV and were in remission period for at least eight week were evaluated. Impulsivity was evaluated with the Barrat Impulsivity Scale, self-esteem was evaluated with the Rosenberg self-esteem scale and affective temperament was evaluated with the Temperament Evaluation of the Memphis, Pisa, Paris, and San Diego Autoquestionnaire. Results: A moderate inverse relation was found between impulsivity and self-esteem. This relation was stronger in women than men. Impulsivity was found to be moderately related with depressive and anxious temparements and strongly related with cyclothymic and irritable temparements. There was no relation between impulsivity and hyperthymic temperament. A moderate level relation was found between self-esteem and hyperthymic temperament. This relation was stronger in men than women. Conclusion: Self-esteem, impulsivity and temperament are differentially related to gender in bipolar patients.
Title Health insurance and healthcare utilisation for Shenzhenresidents : A tale of registrants and migrants ?

Background: Shenzhen’s rapid growth and urbanisation has attracted a large, mobile, migrant working population. This article explores health protection through the means of social health insurance between migrants and registrants and their point of access to healthcare. Methods: A cross-sectional questionnaire survey was conducted in Shenzhen, with a random sample of 793 registered and 750 non-registered residents. Chi-square test and multivariate logistic regression were applied to analyse the association between health insurance coverage with Hukou registration status and healthcare utilisation. Results: Amongst 1543 respondents, 43.1% of non-registered residents were uninsured. Being non-registered strongly predicted for no insurance (OR = 5.00; CI 3.53,7.07) and have purchased additional/ private insurance (OR = 2.99; CI 1.66,5.37). Migrants who self-reported chronic health conditions were also more likely to utilise health services in general (OR = 2.77; CI 1.18,6.52). Conclusions: Inadequate health insurance coverage for migrants as observed in Shenzhen remains a challenge for the Chinese health reform. Our results suggest that the current insurance system must seek to include migrants in order to achieve universal coverage and improved health protection for its population.
ALOS-Next/TanDEM-L: A highly innovative SAR mission for global observation of dynamic processes on the earth's surface

ALOS-Next/Tandem-L is a proposal for a highly innovative L-band SAR satellite mission for the global observation of dynamic processes on the Earth's surface with hitherto unparalleled quality and resolution. It is based on a collaboration between DLR and JAXA which started with a pre-phase A study in 2013 and is currently undergoing a phase A study. Thanks to the novel imaging techniques and the vast recording capacity with up to 8 Tbytes/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere. By this, the new L-band SAR mission will make an essential contribution for a better understanding of the Earth system and its dynamics. ALOS-Next/Tandem-L will, moreover, open new opportunities for risk analysis, disaster management and environmental monitoring by employing especially designed acquisition modes and techniques in combination with a reconfigurable tandem satellite configuration and an L-band SAR instrument with advanced digital beamforming techniques.
Software tools for profile analysis of multi-layered systems by using the Elastic Peak Electron Spectroscopy

The new generation of spectrometers with high energy resolution can resolve elastic peaks of electrons reflected by atoms in solids. In this regard, there is an increasing interest in the applications of the so-called Elastic Peak Electron Spectroscopy (EPES) for measuring composition-versus-depth profiles since it is non-destructive and sensible to the presence of hydrogen in solids. This study presents numerical tools for quantitative interpretation of the EPES signal. They include modules for peak detecting, estimating the elastic peak intensities and retrieving composition-versus-depth profiles. The latter is based on the transport theory and invokes the straight line approximation (SLA). The examples of profile retrieval using the SLA are given. The accuracy of the proposed model is analyzed.
Fine-Grained Chinese Discourse Relation Labelling

This paper explores several aspects together for a fine-grained Chinese discourse analysis. We deal with the issues of ambiguous discourse markers, ambiguous marker linkings, and more than one discourse marker. A universal feature representation is proposed. The pair-once postulation, cross-discourse-unit-first rule and word-pair-marker-first rule select a set of discourse markers from ambiguous linkings. Marker-Sum feature considers total contribution of markers and Marker-Preference feature captures the probability distribution of discourse functions of a representative marker by using preference rule. The HIT Chinese discourse relation treebank (HIT-CDTB) is used to evaluate the proposed models. The 25-way classifier achieves 0.57 micro-averaged F-score.
A COMPUTER VISION SYSTEM TO READ METER DISPLAYS

Since the beginning of the movement for quality management programs based on ISO 9000 or/and ISO/IEC 17025 that were adopted by many type of industries, calibration laboratories have been under pressure to increase productivity. This work is about a computational system to automate the entire instrument calibration process. The computer vision system proposed is to be used to read the display of both analogue as well as digital instruments that do not have communication interfaces to computers such as GPIB or RS-232. In order to figure out instrument indication, the system employs an optical character recognition technique in digital displays and Canny’s method for edge detection and the Hough’s transform method for line localization in analogue displays, accelerating the data acquisition process and makes it less prone to errors. Consequently, it contributes to improve calibration and reduce costs, increasing the number of instruments with quality assured measurements.
Structured Regularization for Large Vector Autoregression

The vector autoregression (VAR), has long proven to be an effective method for modeling the joint dynamics of macroeconomic time series as well as forecasting. One of the major disadvantages of the VAR that has hindered its applicability is its heavy parameterization; the parameter space grows quadratically with the number of series included, quickly exhausting the available degrees of freedom. Consequently, forecasting using VARs is intractable for low-frequency, high dimensional macroeconomic data. However, empirical evidence suggests that VARs which incorporate more component series tend to result in more accurate forecasts than their smaller counterparts. Existing methods which allow for the estimation of large VARs either tend to require ad-hoc specifications or are computationally intractable. We adapt several prominent scalar regression regularization techniques to a vector time series context to greatly reduce the parameter space of VARs. We formulate convex optimization procedures that are amenable to efficient solutions for the time ordered high-dimensional problems we aim to solve. Through this framework, we propose a structured family of models and provide implementations which allow for both the efficient estimation and accurate forecasting of high-dimensional VARs. We demonstrate their efficacy in simulated data examples as well as an application to a large set of macroeconomic indicators. ∗PhD Student, Department of Statistical Science, Cornell University, 301 Malott Hall, Ithaca, NY 14853 (E-mail: wbn8@cornell.edu; Webpage: http://www.wbnicholson.com) †Assistant Professor, Department of Statistical Science and Department of Social Statistics, Cornell University, 1196 Comstock Hall, Ithaca, NY 14853, (E-mail: matteson@cornell.edu; Webpage: https://courses.cit.cornell. edu/~dm484/) ‡Assistant Professor, Department of Biological Statistics and Computational Biology and Department of Statistical Science, Cornell University, 1178 Comstock Hall, Ithaca, NY 14853 (E-mail: jbien@cornell.edu; Webpage: http://faculty.bscb.cornell.edu/~bien/)
A Learning Method to Determine How to Approach an Unknown Object to be Grasped

We present a learning algorithm to determine the appropriate approaching pose to grasp a novel object. Our method focuses on the computation of valid end-effector orientations in order to make contact with the object at a given point. The system achieves this goal by generalizing from positive examples provided by a human operator during an offline training session. The technique is feature-based since it extracts salient attributes of the object to be grasped rather than relying on the availability of models or trying to build one. To compute the desired orientation, the robot performs three steps at run time. Using a multi-class Support Vector Machine (SVM), it first classifies the novel object into one of the object classes defined during training. Next, it determines its orientation, and, finally, based on the classification and orientation, it extracts the most similar example from the training data and uses it to grasp the object. The method has been implemented on a full-scale humanoid robotic torso equipped with multi-fingered hands and extensive results corroborate both its effectiveness and real-time performance.
Fission-Fusion Dynamics New Research Frameworks by Filippo Aureli

Renewed interest in fission-fusion dynamics is due to the recognition that such dynamics may create unique challenges for social interaction and distinctive selective pressures acting on underlying communicative and cognitive abilities. New frameworks for integrating current knowledge on fissionfusion dynamics emerge from a fundamental rethinking of the term “fission-fusion” away from its current general use as a label for a particular modal type of social system (i.e., “fission-fusion societies”). Specifically, because the degree of spatial and temporal cohesion of group members varies both within and across taxa, any social system can be described in terms of the extent to which it expresses fission-fusion dynamics. This perspective has implications for socioecology, communication, cognitive demands, and human social evolution.
Diversity of Juvenile Anadromous Salmonid Assemblages in Coastal Oregon Basins with Different Levels of Timber Harvest

Abstract We examined the relationships of timber harvest, stream habitat complexity, and diversity of juvenile anadromous salmonid assemblages in 14 small- to intermediate-sized basins in coastal Oregon between 1985 and 1989. Diversity (the inverse of a species dominance index) of assemblages in streams in basins with low harvest levels (≤25% of the basin area harvested) was greater than in streams in basins with high harvest levels (>25% of the basin area harvested) (P = 0.02). Assemblages in basins with high levels of harvest were more dominated by a single species than were assemblages in basins with low harvest, Percent of basin harvested was more strongly associated with assemblage diversity (P = 0.07) than were basin area (P = 0.90) or gradient (P = 0.22) when the influence of the other two factors was controlled. Habitat features were compared between three pairs of streams. Streams in basins with low timber harvest had more complex habitat, as manifested by more large pieces of wood per 100 m (P <.
Effectiveness of an algorithm in reducing the number of unnecessary ultrasound scans for deep vein thrombosis: an evaluation report.

INTRODUCTION Patients with suspected deep vein thrombosis (DVT) pose a diagnostic dilemma to the Emergency Department (ED) clinician. This study aimed to implement a known algorithm incorporating the modified Wells criteria and D-dimer testing to guide the ED clinician, thus reducing unnecessary ultrasound scans (USS). METHODS Patients who presented to the ED between August 2008 and April 2009 with suspected DVT underwent Wells scoring. Those with scores < 2 were deemed unlikely to have DVT and underwent D-dimer testing first. Patients with scores ≥ 2 were regarded as likely to have DVT and underwent urgent USS. USS findings were tabulated as positive or negative/indeterminate for DVT. The latter group was followed up for one year to check whether DVT was missed during the initial USS. RESULTS 75 patients presented with suspected DVT and underwent USS. Of these, 14 results were positive and 61 were negative. 37 patients had Wells scores < 2, with three (8.1%) having DVT. Another 38 patients had Wells scores ≥ 2, with 11 (28.9%) having DVT. D-dimer testing was performed on 27 of the 75 patients. Those with DVT had higher average values compared to those without DVT (1.305 vs. 0.595 µg/ml). The majority of patients with raised D-dimer values had cellulitis, although three also had DVT (with values ≥ 0.99 µg/ml). CONCLUSION We managed to reduce the number of unnecessary USS and increase the pick-up rate of DVT. A cut-off score ≥ 2 in our algorithm is suitable for use in the ED setting.
An Assessment of Written/Interactive Dialogue for Information Retrieval Applications

For the foreseeable future, natural language access to databases and other information systems will require the exchange of written messages between the system and user. Such written/interactive dialogue is unique, having the qualities of both written text and spoken discourse yet, also, differing significantly from both. In the present study, we used "Wizard of Oz" techniques to elicit written/interactive dialogue for information retrieval purposes. Our objectives in doing this were (a) to assess the general nature and prevalence of linguistic and dialogue phenomena within the written/interactive register and (b) to determine the impact of user interface shortcuts, such as precanned messages and patterned output, on both the complexity of written/interactive dialogue and general measures of user satisfaction. Our findings indicate that written/interactive dialogue for information retrieval would be very feasible. In spite of slow system response times, subjective reactions from the users were positive, the size of the lexicon used in the dialogues was small, the dialogues decomposed readily into hierarchical structures, and the number and distribution of anaphors were also rather reasonable. Two independent variables were also manipulated: (a) the degree of prefamiliarization given to participants about the base of travel information they would be accessing (i.e., the primer variable) and (b) the degree of constraint on the Wizard's ability to formulate natural language responses to the user (i.e., the natural language output variable). Failure to provide either a primer or a realistic, human natural language output made the dialogues more complex in a number of different ways.