Miracle-dz/UniFAR-FTUs huggingface dataset:
Well-Being and Participation: Views on Policy Measures in Sparsely Populated Rural Municipalities in Finland

Abstract This article examines how do municipalities aim to promote well-being in sparsely populated rural villages, and how are villagers involved in the measures of well-being undertaken in their municipality. The main analysis is based on the interviews of municipal representatives in the case study of North Karelia, Finland. The analysis of well-being and participation, and their relation to the social inclusion of rural inhabitants is executed under the themes of mobility, services, democratic involvement and civic action. The policy measures seek to improve liveability of the environment and the villagers’ quality of life. Participation, as a means and an end of well-being and inclusion, involves the dimensions of structural inclusion, as well as genuine participation and citizen engagement.
SPECT study of Chinese schizophrenic patients suggests that cerebral hypoperfusion and laterality exist in different ethnic groups

Hypofrontality is a common finding in schizophrenia in many countries. To date, there have been few studies on Chinese patients with schizophrenia. We thus wondered whether hypofrontality exists in Chinese patients with schizophrenia. We investigated 45 patients with schizophrenia and 21 healthy controls using brain perfusion single photon emission computed tomography (SPECT). Subjects were also administered the Brief Psychiatric Rating Scale (BPRS), Scale for the Assessment of Positive Symptoms (SAPS), Scale for the Assessment of Negative Symptoms (SANS), Halstead–Reitan Neuropsychological Battery (HRNB) and the Wechsler Memory Scale-Revised (WMS-R). Images were analyzed using a semi-quantitative reading and a quantified region of interest analysis. We found that schizophrenic patients showed hypoperfusion in the frontal and temporal lobes and hyperperfusion in the basal ganglia. Schizophrenic patients with both negative and positive symptoms showed asymmetric perfusion in the temporal lobe. Schizophrenic patients with prominent negative symptoms also showed asymmetric perfusion in the prefrontal lobes. Negative symptoms showed a significantly negative correlation with regional cerebral blood flow (rCBF) in the left frontal lobe. Improved memory quotient (MQ) was significantly correlated with increased rCBF in the left temporal lobe. These findings from Chinese patients confirm a similar regional neuroanatomic dysfunction as in Western patients with the disease.
Widespread protein sequence similarities: origins of Escherichia coli genes

To learn more about the evolutionary origins of Escherichia coli genes, we surveyed systematically for extended sequence similarities among the 1,264 amino acid sequences encoded by chromosomal genes of E. coli K-12 in SwissProt release 26 by using the FASTA program and imposing the following criteria: (i) alignment of segments at least 100 amino acids long and (ii) at least 20% amino acid identity. Altogether, 624 extended alignments meeting the two criteria were identified, corresponding to 577 protein sequences (45.6% of the 1,264 E. coli protein sequences) that had an extended alignment with at least one other E. coli protein sequence. To exclude alignments of questionable biological significance, we imposed a high threshold on the number of gaps allowed in each of the 624 extended alignments, giving us a subset of 464 proteins. The population of 464 alignments has the following characteristics expressed as median values of the group: 254 amino acids in the alignment, representing 86% of the length of the protein, 33% of the amino acids in the alignment being identical, and 1.1 gaps introduced per 100 amino acids of alignment. Where functions are known, nearly all pairs consist of functionally related proteins. This implies that the sequence similarity we detected has biological meaning and did not arise by chance. That a major fraction of E. coli proteins form extended alignments strongly suggests the predominance of duplication and divergence of ancestral genes in the evolution of E. coli genes. The range of degrees of similarity shows that some genes originated more recently than others. There is no evidence of genome doubling in the past, since map distances between genes of sequence-related proteins show no coherent pattern of favored separations.
Recovery function of electrically evoked compound action potential in implanted children with auditory neuropathy: preliminary results

Abstract Conclusion: The results of this study show that the temporal processing ability in children with auditory neuropathy (AN) can be restored to some degree by electrical stimulation through a cochlear implant. In addition, the electrically evoked compound action potential (ECAP) may be a useful index to predict outcomes in implanted children with AN. Objectives: The purpose of this study was to evaluate restoration of the temporal processing abilities in implanted children with AN using ECAP recovery function and speech perception. Methods: Ten children who had received cochlear implantations participated in this study, including six with AN and four with sensorineural hearing loss (SNHL). ECAP recovery functions were measured, and the slopes of ECAP recovery functions in implanted children with AN were compared with those of implanted children with SNHL. Open-set speech perception test scores of implanted children with AN were compared with those of 78 implanted children with SNHL. Results: The slopes of the ECAP recovery function in children with AN did not differ significantly from those in children with SNHL. The group of children with robust ECAPs showed good postoperative performance. However, the group with no ECAPs showed poor performance.
USING DUAL DRIVE ACTUATION

In this paper, a novel technique to prescribe and control the closing motion of a linkage-driven underactuated finger is presented. Since an underactuated, a.k. a self-adaptive, finger generally only has one actuator for a given number of degrees of freedom, its closing motion before making contact with an object is typically imposed by its mechanical design and cannot be changed once the finger is built. In the literature, several closing motions for underactuated fingers have been proposed each one having its own merits and in each case, associated to a particular mechanical layout. In this work, the authors propose a novel design of a partially compliant underactuated finger based on a dual drive actuation system where two motors, which can be used independently or in combination, move the finger. Each of these motors prescribes a different closing motion which has been selected amongst the most commonly found in the literature. In order to characterize the behavior and performances of this finger, a kinetostatic analysis is carried on and a lumped compliance model is developed. The geometry of the finger is then optimized using a genetic algorithm in order to achieve the desired kinematic motions. INTRODUCTION Robotic hands and grippers have been for a long time a challenging issue in robotics and a rising number of works focus on underactuated fingers. Their simplicity and mechanical self-adaptivity led them to gain in popularity over time. Robotic fingers can be roughly divided in two main categories depending on the relative number of actuators with respect to the number of degrees of freedom (DOF), namely, fully actuated or underactuated. The first type relies on an equal number of actuators and DOF [1, 2]. Underactuated fingers on the other side have less actuators than DOF [3, 4]. Therefore, their kinematic is not fully constrained by the actuator(s) and this gives them the capability of adapting themselves to the object they grasp. To the advantage of having less actuators than their counterparts, underactuated fingers could also generally work with simpler control algorithms and do not need sensors. Cost and weight of selfadaptive hands are therefore typically smaller in comparison to fully and overactuated ones. As mentioned in [5], if the only task that to be achieved is grasping, it should be possible with only one actuator. Most underactuated hands are designed in this fashion and therefore, there is generally only one actuator for a given number of DOF in an underactuated finger. The same reasoning also can be extented to underactuated hands (i.e. several fingers). The mechanism transferring the torque, or the force, of the actuator to each DOF at the output is referred to as the transmission mechanism. In other words, there is generally one actuator for one transmission mechanism for one function for a given number of DOF. The transmission mechanism is then optimized for a certain set of performance parameters. Therefore, the closing motion before making contact with an object is typically imposed by the
Gaussian-product subdivision surfaces

Probabilistic distribution models like Gaussian mixtures have shown great potential for improving both the quality and speed of several geometric operators. This is largely due to their ability to model large fuzzy data using only a reduced set of atomic distributions, allowing for large compression rates at minimal information loss. We introduce a new surface model that utilizes these qualities of Gaussian mixtures for the definition and control of a parametric smooth surface. Our approach is based on an enriched mesh data structure, which describes the probability distribution of spatial surface locations around each vertex via a Gaussian covariance matrix. By incorporating this additional covariance information, we show how to define a smooth surface via a nonlinear probabilistic subdivision operator based on products of Gaussians, which is able to capture rich details at fixed control mesh resolution. This entails new applications in surface reconstruction, modeling, and geometric compression.
Driver Drowsiness Detection Using Non-Intrusive Technique

Development of safety features to prevent drowsy driving is one of the major technical challenges in the automobile industry. Driving while in drowsy state is a major reason behind road accidents especially in the modern age. Driving when drowsy leads to a higher crash risk than being in alert state. Therefore, by using assistive systems to monitor driver’s level of alertness can be significant to help prevention of accidents. This paper aims towards detection of drivers drowsiness using visual features approach.Driver drowsiness is detected in real time by detecting drivers face and eyes using HAAR-Cascade Classifier and Yawn detection based on Template matching. The system will provide an alert to the driver if the driver is found to be in drowsy state with help of an alarm.
General method for the modification of different BAC types and the rapid generation of BAC transgenic mice

Most genome projects have relied on the sequencing of bacterial artificial chromosomes (BACs), which encompass 100–300 kb of genomic DNA. As a consequence, several thousand BAC clones are now mapped to the human and mouse genome. It is therefore possible to identify in silico a BAC clone that carries a particular gene and obtain it commercially. Given the large size of BACs, most if not all regulatory sequences of a gene are present and can be used to direct faithful and tissue‐specific expression of heterologous genes in vitro in cell cultures and in vivo in BAC‐transgenic mice. We describe here an optimized and comprehensive protocol to select, modify, and purify BACs in order to generate BAC‐transgenic mice. Importantly, this protocol includes a method to generate, within 2 days, complex plasmid cassettes required to modify BACs, and to efficiently modify different types of BACs selected from the two major BAC libraries available. Altogether, using a combination of genomic database analysis, overlap PCR cloning, and BAC recombination in bacteria, our approach allows for the rapid and reliable generation of “pseudo knockin” mice. genesis 38:39–50, 2004. © 2003 Wiley‐Liss, Inc.
Brand Loyalty on the Basis of Olfactory Techniques Using Discriminant Analysis: A Case of Cafe Coffee Day Store in Kolkata, India

Consumers of modern days are concerned with emotional connections along with product attributes during buying. This has led to a whole new advent of sensorial marketing, beginning the era of experiential marketing. Utilizing this opportunity, marketers are tapping the consumer’s emotive sense and exploring the option of attaching sensory cues, like smell, in marketing, thereby use of olfactory cues is increasing in brand differentiation. The aim of this paper is to assess relationship of likability of fragrance with strength of aroma in purchase. The help of a case Cafe Coffee Day (CCD) has been taken to investigate the above as this brand tries to enhance overall in-stay experience of consumers with implementation of Olfactory Branding. This article reflects outcome of a survey using judgemental sampling plan in few selected CCD store in Kolkata, having an atmosphere with strong aroma of coffee. A structured schedule was used to collect data from 200 respondents using appropriate scale with variables chosen from study outcomes of other researchers mentioned in serious academic literatures. The data obtained was treated with classification technique of discriminant analysis exploring the linkage of strength of aroma with likability of fragrance and its relationship with shopping under aromatic conditions. The analysis joins strength of aroma with shopping under aromatic conditions with likability of fragrance both measured under 5 point metric scales and connects it with the non metric variable shopping under aromatic conditions. This shows that there is an influence of fragrance with consumer’s choice and subsequent purchase decision.
Receptor‐mediated transcytosis of botulinum neurotoxin A through intestinal cell monolayers

Botulism is mainly acquired by the oral route, and botulinum neurotoxin (BoNT) escapes the gastrointestinal tract by crossing the digestive epithelial barrier prior to gaining access to the nerve endings. Here, we show that biologically active BoNT/A crosses intestinal cell monolayers via a receptor‐mediated transcytosis, including a transport inhibition at 4°C and a passage at 37°C in a saturable manner within 30–60 min. BoNT/A passage rate was about 10‐fold more efficient through the intestinal crypt cell line m‐ICcl2, than through the carcinoma Caco‐2 or T84 cells, and was not increased when BoNT/A was associated with the non‐toxic proteins (botulinum complex). Like for neuronal cells, BoNT/A binding to intestinal cells was mediated by the half C‐terminal domain as tested by fluorescence‐activated cytometry and by transcytosis competition assay. A ‘double receptor model’ has been proposed in which BoNT/A interacts with gangliosides of GD1b and GT1b series as well as SV2 protein. Gangliosides of GD1b and GT1b series and recombinant intravesicular SV2‐C domain partially impaired BoNT/A transcytosis, suggesting a putative role of gangliosides and SV2 or a related protein in BoNT/A transcytosis through Caco‐2 and m‐ICcl2 cells.
Adenosine 3',5-cyclic monophosphate phosphodiesterase activity in granulosa cells from Booroola x Romney ewes with and without the F gene.

Granulosa cells from ovarian follicles (greater than or equal to 1 mm diameter) in Booroola ewes which are homozygous (FF) or heterozygous (F+) for the F gene have previously been shown to produce significantly more cAMP in response to FSH or LH than those from similar sized follicles in ewes without the F gene (++). The aim of these studies was to test whether these F gene-specific differences arose because of differences in cAMP-phosphodiesterase (cAMP-PDE) activity. In the first study using 1 mumol cAMP/l as substrate, no F gene-specific effects were noted in cAMP-PDE activity in granulosa cells from small (1-2.5 mm diameter, n = 4 per genotype) or large (greater than or equal to 3 mm diameter, n = 4 per genotype) follicles from FF, F+ or ++ ewes, despite F gene-specific effects in FSH (1 microgram/ml)- and LH (0.1 microgram/ml)-induced cAMP accumulation in these same cell preparations. The overall mean levels of cAMP-PDE across all genotypes in cells from small and large follicles were 0.47 +/- 0.04 (S.E.M., n = 12) and 0.28 +/- 0.03 pmol cAMP/10(6) cells per min respectively; the mean PDE activity in cells from small follicles was significantly (P less than 0.05) higher compared with that in cells from large follicles. In a second study, granulosa cells from each genotype were pooled over all follicle sizes (greater than or equal to 1 mm diameter, one pool per genotype) and the rates of cAMP hydrolysis tested over a range of substrate concentrations (0-16 mumol/l) but no gene-specific differences with respect to the Michaelis constant and maximum velocity were noted. (ABSTRACT TRUNCATED AT 250 WORDS)
Retina Impact of Drusen Volume on Quantitative Fundus Autofluorescence in Early and Intermediate Age-Related Macular Degeneration

Gregor Sebastian Reiter, Reinhard Told, Ferdinand Georg Schlanitz, Hrvoje Bogunovic, Lukas Baumann, Stefan Sacu, Ursula Schmidt-Erfurth, and Andreas Pollreisz Vienna Clinical Trial Center (VTC), Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria Christian Doppler Laboratory for Ophthalmic Image Analysis, Vienna Reading Center, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria
Visual Attention-Driven Hyperspectral Image Classification

Deep neural networks (DNNs), including convolutional neural networks (CNNs) and residual networks (ResNets) models, are able to learn abstract representations from the input data by considering a deep hierarchy of layers that perform advanced feature extraction. The combination of these models with visual attention techniques can assist with the identification of the most representative parts of the data from a visual standpoint, obtained through more detailed filtering of the features extracted by the operational layers of the network. This is of significant interest for analyzing remotely sensed hyperspectral images (HSIs), characterized by their very high spectral dimensionality. However, few efforts have been conducted in the literature in order to adapt visual attention methods to remotely sensed HSI data analysis. In this paper, we introduce a new visual attention-driven technique for the HSI classification. Specifically, we incorporate attention mechanisms to a ResNet in order to better characterize the spectral–spatial information contained in the data. Our newly proposed method calculates a mask that is applied to the features obtained by the network in order to identify the most desirable ones for classification purposes. Our experiments, conducted using four widely used HSI data sets, reveal that the proposed deep attention model provides competitive advantages in terms of classification accuracy when compared to other state-of-the-art methods.
Identifying Highly Dense Areas from Raw Location Data

In this paper we show how very high-volumes of raw WiFi-based location data of individuals can be used to identify dense activity locations within a neighbourhood. Key to our methods is the inference of the size of the area directly from the data, without having to use additional geographical information. To extract the density information, data-mining and machine learning techniques form activity-based transportation modelling are applied. These techniques are demonstrated on data from a large-scale experiment conducted in Singapore in which tens of thousands of school children carried a multi-sensor device for five consecutive days. By applying the techniques we were able to identify expected high-density areas of school pupils, specifically their school locations, using only the raw data, demonstrating the general applicability of the methods.
ECE543 Project Paper: Spectrally-normalized margin bounds for neural networks

This paper [Bartlett et al., 2017] proves a generalization bound for neural networks free of explicit ”combinatorial parameters” like depth or number of parameters other than a log factor. This is achieved via a covering number bound for the set of matrices achieved by a fixed matrix times another matrix with bounded norm, which is then applied to bound the Rademacher complexity via chaining. It is shown empirically that the normalized margin, which consists of the margin of the network (akin to yf(x) for binary classification, but modified for multiclass) divided by the Rademacher complexity (in other words, the inverse of the Rademacher complexity of the function class composed with ramp loss with corresponding margin parameter) captures how difficult a dataset is to learn. More precisely, by calculating the normalized margin of each input point and plotting the resulting distribution, one can gauge the difficulty of the classification problem. A hard problem corresponds to a distribution further to the left. In this report I will present the proof of the paper’s result in a self-contained manner, leaving some proofs to the appendix. The proofs are essentially the same as in the paper, except Lemma 3.2 is very slightly generalized with a negligible modification to the proof (‖X‖p is allowed to be ‖X‖p,p′ with (p′, q) conjugate exponents). Also, because the empirical Rademacher complexity is used there is no need to state Lemma A.8 in terms of a bound on the data norm ‖X‖2 like in the paper, and thus no need to include data norm bounds in the union bound in Lemma A.9. Thus, unlike the paper ‖X‖2 is included in the bounds immediately. Also, there seems to be a slight bug in the paper when doing the union bound in Lemma A.9 – they assume that j1 ≥ 2, i.e. γ ≤ n2 without giving a proper justification. Instead I increased the range of j1 to all integers. Then, I will compare the paper’s result with the neural network generalization bounds from the course notes, after translating the framework of the course notes to a more typical neural net framework. I will briefly discuss how Golowich et al. [2017], which a bound in the notes is derived from, mentions this paper in an arguably wrong way. Finally, I will discuss how it seems inevitable that the matrix covering lemma was used in the way it was by the paper.
Repetitive stretch induces c-fos and myogenin mRNA within several hours in skeletal muscle removed from rats.

OBJECTIVE To investigate what effect repetitive stretch has on gene transcription in muscle tissues removed from rats. DESIGN Case-control study. SETTING University laboratory. ANIMALS Eight female 8-week-old Wistar rats. INTERVENTIONS Rat anterior tibial and soleus muscles were removed and repetitively stretched about 20% of the muscle length by using the Magnus method in Krebs-Ringer solution. Stretch-relax cycles 15 times per minute were continued for 2 hours in 1 group and 4 hours in another group. Contralateral muscles removed from the same rat were incubated without stretch as the control. MAIN OUTCOME MEASURES After repetitive stretch, total ribonucleic acid (RNA) was extracted from the muscles and Northern blotting was carried out using c-fos and myogenin oligonucleotide as probes. RESULTS Repetitive stretch during 2 hours significantly increased the expression of c-fos messenger RNA (mRNA) in both the tibialis anterior and soleus muscles. Increased expression of myogenin mRNA in both muscles was observed with repetitive stretch for 4 hours. Because of the initial increase of immediate early gene c-fos mRNA and the subsequent increase of myogenic transcription factor myogenin mRNA, it appears that repetitive muscle stretch induces sequential progression of gene transcription toward muscle hypertrophy. CONCLUSIONS Mechanical repetitive stretch for a few hours would be one of the stimulating factors for muscle growth and should be available for muscle training in clinical rehabilitation.