LLukas22/scidocs huggingface dataset:
Oral and respiratory control for preterm feeding.

PURPOSE OF REVIEW
Feeding competency is a frequent and serious challenge to the neonatal intensive care unit survivors and to the physician-provider-parent teams. The urgency of effective assessment and intervention techniques is obviated to promote safe swallow, as attainment of oral feeding for the preterm infant/newborn is one of the prerequisites for hospital discharge. If left unresolved, feeding problems may persist into early childhood and may require management by pediatric gastroenterologists and feeding therapists. This review highlights studies aimed at understanding the motor control and development of nonnutritive and nutritive suck, swallow, and coordination with respiration in preterm populations.


RECENT FINDINGS
Functional linkages between suck-swallow and swallow-respiration manifest transitional forms during late gestation and can be delayed or modified by sensory experience and/or disease processes. Moreover, brainstem central pattern generator (CPG) networks and their neuromuscular targets attain functional status at different rates, which ultimately influences cross-system interactions among individual CPGs. Entrainment of trigeminal primary afferents to activate the suck CPG is one example of a clinical intervention to prime cross-system interactions among ororhythmic pattern generating networks in the preterm and term infants.


SUMMARY
The genesis of within-system CPG control for rate and amplitude scaling matures differentially for suck, mastication, swallow, and respiration. Cross-system interactions among these CPGs represent targets of opportunity for new interventions that optimize experience-dependent mechanisms to promote robust ororhythmic patterning and safe swallows among preterm infants.
Blocks That Shout: Distinctive Parts for Scene Classification

The automatic discovery of distinctive parts for an object or scene class is challenging since it requires simultaneously to learn the part appearance and also to identify the part occurrences in images. In this paper, we propose a simple, efficient, and effective method to do so. We address this problem by learning parts incrementally, starting from a single part occurrence with an Exemplar SVM. In this manner, additional part instances are discovered and aligned reliably before being considered as training examples. We also propose entropy-rank curves as a means of evaluating the distinctiveness of parts shareable between categories and use them to select useful parts out of a set of candidates. We apply the new representation to the task of scene categorisation on the MIT Scene 67 benchmark. We show that our method can learn parts which are significantly more informative and for a fraction of the cost, compared to previous part-learning methods such as Singh et al. [28]. We also show that a well constructed bag of words or Fisher vector model can substantially outperform the previous state-of-the-art classification performance on this data.
Food deprivation explains effects of mouthbrooding on ovaries and steroid hormones, but not brain neuropeptide and receptor mRNAs, in an African cichlid fish

Feeding behavior and reproduction are coordinately regulated by the brain via neurotransmitters, circulating hormones, and neuropeptides. Reduced feeding allows animals to engage in other behaviors important for fitness, including mating and parental care. Some fishes cease feeding for weeks at a time in order to provide care to their young by brooding them inside the male or female parent's mouth. Maternal mouthbrooding is known to impact circulating hormones and subsequent reproductive cycles, but neither the full effects of food deprivation nor the neural mechanisms are known. Here we ask what effects mouthbrooding has on several physiological processes including gonad and body mass, brain neuropeptide and receptor gene expression, and circulating steroid hormones in a mouthbrooding cichlid species, Astatotilapia burtoni. We ask whether any observed changes can be explained by food deprivation, and show that during mouthbrooding, ovary size and circulating levels of androgens and estrogens match those seen during food deprivation. Levels of gonadotropin-releasing hormone 1 (GnRH1) mRNA in the brain were low in food-deprived females compared to controls and in mouthbrooding females compared to gravid females. Levels of mRNA encoding two peptides involved in regulating feeding, hypocretin and cholecystokinin, were increased in the brains of food-deprived females. Brain mRNA levels of two receptors, GnRH receptor 2 and NPY receptor Y8c, were elevated in mouthbrooding females compared to the fed condition, but NPY receptor Y8b mRNA was differently regulated by mouthbrooding. These results suggest that many, but not all, of the characteristic physiological changes that occur during mouthbrooding are consequences of food deprivation.
An ultra low-voltage ultra low power rail-to-rail CMOS OTA Miller

This work describes a simple topology to implement a low voltage rail-to-rail CMOS Miller OTA with differential pair using DC shifters and bulk driven inputs. The transistors work on weak inversion and the topology requires a 600 mV power supply and consumes only 420 nW on the 0.35 /spl mu/m TSMC CMOS process. The voltage swing and the frequency response are almost independent of the power supply voltage ranging from 600 mV to 3.3 V.
Efficacy of methylphenidate for the treatment of mental sequelae after traumatic brain injury

BACKGROUND
This study aimed to evaluate the effect of methylphenidate for treating mental sequelae after traumatic brain injury (TBI).


METHODS
Thirty-six patients with TBI were randomly divided into the intervention group and placebo group. The participants in the intervention group received methylphenidate, while subjects in the placebo group were administered a placebo. This study was conducted from January 2014 to December 2016. The outcome measurements included Mental Fatigue Scale, Choice Reaction Time, Compensatory Tracking Task, Mental Arithmetic Test, Digit Symbol Substitution Test, Mini-Mental State Examination (MMSE), Beck Depression Inventory (BDI), and Hamilton Rating Scale for Depression. In addition, safety was also recorded and assessed.


RESULTS
A total of 33 subjects completed the study. Methylphenidate showed greater efficacy than placebo, with decreased scores on the Mental Fatigue Scale, Choice Reaction Time, and Compensatory Tracking Task in the intervention group compared to the placebo group (P < .01, respectively). Furthermore, increased scores on the Mental Arithmetic Test, Digit Symbol Substitution Test, and MMSE in the intervention group, compared to those in the placebo group (P < .01 respectively), were observed. In addition, a significant difference in the scores on the BDI (P = .04) and Hamilton Rating Scale for Depression (P = .005) was observed between the 2 groups. The safety at the end of the 30 week-treatment was similar between the 2 groups (P > .05).


CONCLUSION
The results of this study demonstrated that methylphenidate could effectively improve mental fatigue and cognitive functions in patients with TBI.
Twenty-four hour hypothermic machine perfusion preservation of porcine pancreas facilitates processing for islet isolation.

Procurement of donor pancreata for islet isolation and transplantation is not yet widely practiced due to concerns about the impact of postmortem ischemia on functional islet yields. Perfusion/preservation technology may help to circumvent ischemic injury as applied in this study of porcine pancreata prior to islet isolation. Pancreata harvested from adult pigs were assigned to 1 of 3 preservation treatment groups: G1, fresh controls, processed immediately with minimum cold ischemia (<1 hour); G2, static cold storage, flushed with cold UW-Viaspan and stored at 2 degrees -4 degrees C for 24 hours; and G3, hypothermic machine perfusion (HMP) on a pulsatile LifePort machine Organ Recovery Systems, Inc., Des Plaines, Ill, United States with KPS1 solution at 4-7 degrees C and low pressure (10 mm Hg) for 24 hours. Islet isolation was then accomplished using conventional methods. Product release criteria were used to assess islet yield and function. Islet yield was markedly different between the treatment groups. There was a statistically significant increased yield in the HMP group over static cold storage in UW-Viaspan (P < .05). Functionally, the islets from each experimental group were equivalent and not significantly different from fresh controls (G1). Dithizone staining of islets showed consistently more uniform digestion of pancreata from G3 compared with G1 and G2, with greater separation of the tissue and fewer entrapped islets. HMP for 24 hours was well tolerated, leading to moderate edema but no loss of function of the harvested islets. The edema appeared to aid in enzymatic digestion, producing a greater yield and purity of islets compared with pancreata subjected to 24 hours of static cold storage.
Association Rules Mining : A Recent Overview

In this paper, we provide the preliminaries of basic concepts about association rule mining and survey the list of existing association rule mining techniques. Of course, a single article cannot be a complete review of all the algorithms, yet we hope that the references cited will cover the major theoretical issues, guiding the researcher in interesting research directions that have yet to be explored.
Spread spectrum modulation and signal masking using synchronized chaotic systems

Chaotic dynamical systems are nonlinear deterministic systems which often exhibit erratic and irregular behavior. The signals that evolve in these systems are typically broadband, noise-like and similar in many respects to a stochastic process. Because of these properties chaotic signals potentially provide an important class of signals which can be utilized in various communications, radar and sonar contexts for masking information-bearing waveforms and as modulating waveforms in spread spectrum systems. Recently, it has been demonstrated that the chaotic Lorenz and Rssler systems can be decomposed into a drive system and a stable response subsystem which will synchronize when coupled with a common drive signal. This property has several practical applications and suggests novel approaches to secure communication and signal masking. In addition to the Lorenz and R6ssler systems, we discuss and demonstrate that the continuous-time Double Scroll system and discrete-time Henon map are also decomposable into synchronizing subsystems. We then propose and explore in a preliminary way how synchronized chaotic systems can be used for spread spectrum communication and for various signal masking purposes.
A Methodology for Analyzing Political Speech: Western Approaches to Rhetorical Theory

Rhetorical scholars have long been interested in studying the internal dynamics of political speech − not summarizing what is said, but rather describing how a speech works as a rhetorical appeal.1 In so doing, of course, one naturally examines the content of the discourse (its goals and strategies) in order to understand how the speaker seeks to influence an audience and to evaluate both the effectiveness of the speech as a rhetorical appeal and its ethical and political implications. In contemporary pluralistic societies such as Germany, Great Britain, and the United States—where political voices have access to multiple forms of communication, including television, radio, newspapers, scholarly journals, and Internet driven social media—it is expected that any national level political event will be commented upon and analyzed by both adherents and opponents. Never is this more true than when the leader of a nation, or a candidate to become that leader, speaks in any public forum. Speeches by American political leaders are routinely subjected to intensive rhetorical criticism. Just within the past few years, for instance, The Quarterly Journal of Speech has published rhetorical criticism focusing on speeches by Barack Obama (twice), Franklin Roosevelt, and Mohammad Ali. In this paper, which is aimed at presenting Western methods of rhetorical analysis to students and teachers in Russia, we have chosen to apply those methods to the most recent inaugural address given by the newly elected President of the Russian Federation, Vladimir Vladimirovich Putin, on the assumption that most readers will be familiar with that speech.
Clinician judgment vs formal scales for predicting intracerebral hemorrhage outcomes.

OBJECTIVE
To compare the performance of formal prognostic instruments vs subjective clinical judgment with regards to predicting functional outcome in patients with spontaneous intracerebral hemorrhage (ICH).


METHODS
This prospective observational study enrolled 121 ICH patients hospitalized at 5 US tertiary care centers. Within 24 hours of each patient's admission to the hospital, one physician and one nurse on each patient's clinical team were each asked to predict the patient's modified Rankin Scale (mRS) score at 3 months and to indicate whether he or she would recommend comfort measures. The admission ICH score and FUNC score, 2 prognostic scales selected for their common use in neurologic practice, were calculated for each patient. Spearman rank correlation coefficients (r) with respect to patients' actual 3-month mRS for the physician and nursing predictions were compared against the same correlation coefficients for the ICH score and FUNC score.


RESULTS
The absolute value of the correlation coefficient for physician predictions with respect to actual outcome (0.75) was higher than that of either the ICH score (0.62, p = 0.057) or the FUNC score (0.56, p = 0.01). The nursing predictions of outcome (r = 0.72) also trended towards an accuracy advantage over the ICH score (p = 0.09) and FUNC score (p = 0.03). In an analysis that excluded patients for whom comfort care was recommended, the 65 available attending physician predictions retained greater accuracy (r = 0.73) than either the ICH score (r = 0.50, p = 0.02) or the FUNC score (r = 0.42, p = 0.004).


CONCLUSIONS
Early subjective clinical judgment of physicians correlates more closely with 3-month outcome after ICH than prognostic scales.
Context-dependent group size choice in fish

The costs and benefits of group membership vary with the size of groups, and individuals are expected to modify their choice of groups in response to ecological factors such as food availability and predation risk. We experimentally examined context-dependent group size choice in a shoaling fish, the banded killifish, Fundulus diaphanus, by using nondirectional odour cues to simulate a food source or a successful attack by a predator (food or alarm treatments) in the laboratory. Group sizes were significantly smaller in the food treatment and larger in the alarm treatment than in control trials. When presented with food and alarm cues together, fish formed groups that were larger than control groups but smaller than those seen with alarm cues alone. These results are consistent with theoretical predictions based on the known benefits and costs of grouping and with previous laboratory work examining the individual shoal choice behaviour of single fish. To examine possible mechanisms of group formation, we developed an individual-based model of shoaling behaviour in which simulated fish were allowed to modify the area over which they interacted with neighbouring individuals. Group size distributions produced by the model were a good approximation of our experimental data. We suggest that local behavioural interaction rules of this type are a potential mechanism by which fish may individually adjust grouping behaviour without requiring extensive information on the position and movement of all possible shoalmates.
Shopping mode choice : Physical store shopping versus e-shopping

This study aims to explore how consumers evaluate these time attributes; i.e., the value of time, when they are facing a shopping mode choice between physical store shopping and e-shopping. For this purpose, it conducts an experiment to acquire data on respondents’ stated preference choices between physical bookstore shopping and online bookstore shopping. It is finally found that the value of delivery time for a purchased book from an online bookstore to a consumer is approximately $0.53 per day, which means an online bookstore will have to lower a book’s price by $0.53 to attract a physical bookstore shopper if the delivery is delayed for one day. It is also found that in terms of monetary values, avoiding a shopping trip produces far more benefits than bearing waiting for the delivery of books for an online purchase. 2008 Elsevier Ltd. All rights reserved.
Renal Function - Estimation of Glomerular Filtration Rate

Kratak sadr`aj: Brzina glomerularne filtracije (GFR) je {iroko prihva}ena kao najbolja op{ta mera funkcije bubrega. Vodi~i ameri~ke Nacionalne fondacije za bubreg defini{u hroni~nu bubre`nu bolest (HBB) bilo sa vredno{}u GFR koja je manja od 60 mL/min/1,73 m2 ili sa prisustvom o{te}enja bubrega, bez obzira na uzrok, u toku 3 ili vi{e meseci i klasifikuju stadijume te`ine HBB prema GFR. GFR se mo`e meriti kao urinarni ili plazma klirens egzogenih filtracionih markera kao {to je inulin. Me|utim, zbog te{ko}a u primeni, tro{kova i radijacionog izlaganja, ove metode imaju ograni~enu upotrebu u rutinskim laboratorijama. Klirens kreatinina mo`e biti korisna alternativa kada egzogeni markeri nisu dostupni, ali sakupljanje urina u vremenskim intervalima nije pogodno za pacijente i osetljivo je na gre{ku pri sakupljanju. GFR se ~esto procenjuje klini~ki iz serumskih koncentracija egzogenog kreatinina ili cistatina C. Cistatin C u serumu jo{ uvek nije adekvatno procenjen kao indeks GFR, a na kreatinin u serumu uti~u GFR i faktori nezavisni od GFR, uklju~uju}i godine, pol, rasu, telesnu veli~inu, ishranu, izvesne lekove i laboratorijske analiti~ke metode. Prema klini~kim vodi~ima Nacionalne fondacije za bubreg, klini~ke laboratorije bi trebalo da izdaju »procenjenu« GFR (estimated GFR), izra~unatu iz prediktivnih jedna~ina, kao dodatak izve{tavanja vrednosti markera u serumu. Trenutno preporu~ena jedna~ina za procenu je razvijena iz MDRD (Modification of Diet in Renal Disease) studije. Ova jedna~ina koristi godine, pol, rasu (afro-ameri~ka prema ne-afro-ameri~koj) i koncentraciju kreatinina u serumu, a ne zahteva varijablu za telesnu te`inu zato {to normalizuje GFR za standardnu telesnu povr{inu od 1,73 m2. Da bi se postigla pobolj{ana ta~nost prera~unate GFR sa ovom jedna~inom, preporu~uje se da komercijalne metode za kreatinin budu kalibrisane prema sertifikovanim referentnim materijalima i sledljive sa IDMS (isotope dilution mass spectrometry) metodologijom. Za MDRD jedna~inu je pokazano da je korisna za pacijente sa HBB, ali njena upotreba je jo{ uvek nejasna za ljude sa niskim vrednostima kreatinina u serumu i visokim vrednostima za GFR, uklju~uju}i zdrave pojedince, decu i trudnice. Validacione studije su u razvoju kako bi se procenila MDRD jedna~ina za druge etni~ke grupe i razli~ita bolesna stanja.
A Development Platform for Integrating Wireless Devices and Sensors into Ambient Intelligence Systems

Architecture, HYDRA will enable the development of generic services based on open standards. I. DEVELOPING MIDDLEWARE TO ENABLE SOFTWARE DEVELOPERS TO CREATE SERVICES FOR EMBEDDED SYSTEMS Embedded Systems are everywhere, built into healthcare devices, into building automation, heating systems and home appliances, into mobile phones and communication, into cars, roads, bridges and tunnels, and even into our clothes. They are interconnected into networks of many devices and they form the building blocks of the future Internet of Things. Embedded Systems technologies are deployed in all relevant market sectors and have a major impact on the way these sectors work and collaborate, how they will develop, and how successful their products will be on the world market. Manufacturers are thus increasingly seeking to network their own products with other systems in order to provide higher value-added solutions for their customers – often a difficult, time consuming and costly development process, in particular for SME's. The HYDRA project aims to alleviate the problems facing European industries by researching and developing middleware for networked embedded systems that allows developers to develop cost-effective, high-performance Ambient Intelligence (AmI) applications using heterogeneous physical devices. Middleware is software that connects different components or applications to enable multiple processes running on one or more machines to interact across a network. The 52 months Hydra project is working on developing middleware that allows developers to create ambient intelligence applications, i.e. electronic environments that are sensitive and responsive to the presence of people. HYDRA will showcase its prototype for secure home automation. This will demonstrate how future ambient environments can be designed, realised and integrated. It will also allow users and developers to provide their input and feedback. II. HYDRA The HYDRA project [1] develops middleware for networked embedded systems that allows developers to create ambient intelligence applications utilizing device and sensor networks. Device and sensor networking research has seen increasing activity in the last years, with advances in sensor node and radio hardware [2] [3]. This work has been instrumental in clarifying the trade-off between computation and communication and the need for in-network processing. Most of this work is based on topographically addressed sensor nodes; other researchers (Heideman et. al. [4]) have based their work on the use of attribute-based naming for structure and data diffusion. The use of attribute-based naming is an interesting concept that will be further investigated in HYDRA. Internet ad hoc routing (Broch et al. …
Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease

OBJECTIVE
We present the PaHaW Parkinson's disease handwriting database, consisting of handwriting samples from Parkinson's disease (PD) patients and healthy controls. Our goal is to show that kinematic features and pressure features in handwriting can be used for the differential diagnosis of PD.


METHODS AND MATERIAL
The database contains records from 37 PD patients and 38 healthy controls performing eight different handwriting tasks. The tasks include drawing an Archimedean spiral, repetitively writing orthographically simple syllables and words, and writing of a sentence. In addition to the conventional kinematic features related to the dynamics of handwriting, we investigated new pressure features based on the pressure exerted on the writing surface. To discriminate between PD patients and healthy subjects, three different classifiers were compared: K-nearest neighbors (K-NN), ensemble AdaBoost classifier, and support vector machines (SVM).


RESULTS
For predicting PD based on kinematic and pressure features of handwriting, the best performing model was SVM with classification accuracy of Pacc=81.3% (sensitivity Psen=87.4% and specificity of Pspe=80.9%). When evaluated separately, pressure features proved to be relevant for PD diagnosis, yielding Pacc=82.5% compared to Pacc=75.4% using kinematic features.


CONCLUSION
Experimental results showed that an analysis of kinematic and pressure features during handwriting can help assess subtle characteristics of handwriting and discriminate between PD patients and healthy controls.
Machine Learning for Sequential Data: A Review

Statistical learning problems in many fields involve sequential data. This paper formalizes the principal learning tasks and describes the methods that have been developed within the machine learning research community for addressing these problems. These methods include sliding window methods, recurrent sliding windows, hidden Markov models, conditional random fields, and graph transformer networks. The paper also discusses some open research issues.