Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition of Japanese finger spelling gestures using neural networks

Effective communication with the hearing and speech impaired often requires at least a basic working knowledge of sign language gestures, without which a memo pad and pen, or a mobile phone's notepad is indispensable. The aim of this study was to build a neural network that could be used to recognize static finger-hand gestures of the yubimoji, the Japanese sign language syllabary. To build the network, signal inputs from a data glove interface were taken for each of the static yubimoji gestures. The network was trained and tested 10 times using a multilayer perceptron model. Overall, only 18 of the 41 static gestures were successfully recognized. One of the reasons was attributed to the inability of the data glove to measure gesture directions particularly for yubimoji gestures with similar finger configurations. Future work will focus on these problems as well as the inclusion of dynamic yubimoji gestures.
Ensemble of Decision Tree Classifiers for Mining Web Data Streams

The World Wide Web (www or w3 commonly known as the web) is the largest database available with growth at the rate of millions of pages a day and presents a challenging task for mining web data streams. Currently extraction of knowledge from web data streams is getting more and more complex, because the structure of data doesn’t match the attribute-values when considering the large volume of web data. In this paper, an ensemble of decision tree classifiers is presented, which is an efficient mining method to obtain a proper set of rules for extracting knowledge from a large amount of web data streams. We built a web server using Model 2 Architecture to collect the web data streams and applied the ensemble classifier for generating decision rules using several decision tree learning models. Experimental results demonstrate that the proposed method performs well in decision making and predicting the class value of new web data streams.
Cognitive Functioning Self-Assessment Scale (CFSS): Further psychometric data

ABSTRACT The “Cognitive Functioning Self-Assessment Scale” (CFSS) is a questionnaire specifically developed for the self-reporting of cognitive functioning in non-neurologic settings. A previous published study had showed its good reading comprehension and face validity, defining it as monofactorial and reliable. This paper provides further psychometric data and norms derived on a larger sample from the general population. Our work is divided into two studies. In Study 1, 194 adult patients in a General Practitioner study (27.8% retested after 2 weeks) have filled-in the CFSS together with the CES-D, the State Anxiety subscale of the STAI, and a clinical and socio-demographic data form. The Cronbach’s alpha of the CFSS was 0.878; the temporal stability was 0.794; in addition, CFSS showed substantial and moderate associations respectively with depression and state anxiety measures. In Study 2, CFSS data on 476 participants have been considered. CFSS score was associated to age (p < 0.01) and education (p < 0.01). In addition, CFSS descriptive statistics according to age and education levels were provided. In conclusion, although further research is surely necessary to refine the CFSS, the herein presented data together with the already published results, confirm the validity and reliability of this tool.
Advanced neuroimaging in stroke patients: prediction of tissue fate and hemorrhagic transformation

Stroke is the second greatest cause of mortality worldwide after ischemic heart disease. It is also the leading cause of disability in industrialized countries. According to the WHO, 15 million people worldwide suffer a stroke annually. It is very difficult to distinguish between an ischemic and a hemorrhagic stroke on a clinical basis, therefore imaging (computed tomography or MRI) plays a central role in the evaluation of patients with acute stroke symptoms. Because of significant advances over the last decade, imaging now provides information beyond the mere presence or absence of intracerebral hemorrhage. Comprehensive neurovascular imaging protocols using computed tomography or MRI can be acquired within minutes, helping to distinguish stroke etiology and guiding treatment decisions for acute reperfusion therapies. The purpose of this article is to give an overview of diagnostic information provided by neuroimaging in the setting of acute stroke, especially ischemic stroke, including information about brain tissue viability status and blood–brain barrier permeability. We will discuss the indications of the current treatment options for stroke, and how imaging influences treatment decision. We will organize our discussion around the concept of the ‘four Ps’ (parenchyma, pipes, penumbra and permeability) proposed by Howard Rowley, which is an excellent guide for understanding the underlying causes and pathophysiology of ischemic stroke.
Potential role for microfluctuations as a temporal directional cue to accommodation

The goal was to revisit an important, yet unproven notion that accommodative microfluctuations facilitate the determination of direction (sign) of abrupt focus changes in the stimulus to accommodation. We contaminated the potential temporal cues from natural accommodative microfluctuations by presenting uncorrelated external (screen) temporal defocus noise that combined with the retinal image effects of natural microfluctuations. A polychromatic Maltese spoke pattern thus either modulated defocus at a combination of two temporal frequencies (on-screen noise condition) or was static (control condition). The on-screen conditions were combined with step changes in optical vergence that were randomized in direction and magnitude. Five subjects monocularly viewed stimuli through a Badal optical system in a Maxwellian view. An artificial 4-mm aperture was imaged at the entrance pupil of the eye. Wavefront aberrations were measured dynamically at 50 Hz using a custom Shack–Hartmann aberrometer. Dynamic changes in the Zernike defocus term with step changes in optical vergence were analyzed. We calculated the percentage of correct directional responses for 1, 2, and 3 D accommodative and disaccommodative step stimuli using preset criteria for latency, velocity, and persistence of the response. The on-screen noise condition reduced the percent-correct responses compared to the static stimulus, suggesting that this manipulation affected the detectability of the sign of the accommodative stimulus. Several possible reasons and implications of this result are discussed.
Pharmacological and Nonpharmacological Treatment After Cardiac Surgery

Open-heart surgery has become a common procedure. Postcardiac surgery management is a critical issue and represents a crucial period in terms of physical recovery. Cardiac rehabilitation is increasingly considered as an integral component of the continuum of care for patients with cardiovascular disease. Its usefulness is now widely accepted, and therefore, it is recommended in most contemporary cardiovascular clinical practice guidelines. Similarly, early pharmacological management can modulate the pathophysiological alterations after cardiac surgery, leading to an improvement in the early and long-term outcome. In this review, we will present recent advances in postcardiac surgery management, focusing on the pathophysiology of the perioperative period and on recent evidences in pharmacological and rehabilitative strategies.
Genetic identity of the Bemisia tabaci species complex and association with high cotton leaf curl disease (CLCuD) incidence in Pakistan.

BACKGROUND The cotton whitefly, Bemisia tabaci (Gennadius), is a cryptic species complex, and members of the complex have become serious pests in Pakistan because of their feeding and their ability to transmit cotton leaf curl virus (CLCuV). Here, an analysis was made of the identity of B. tabaci collected from cotton and a range of non-cotton hosts in the cotton-growing zones in Punjab and Sindh, the main cotton-producing provinces of Pakistan, using a portion of the mitochondrial cytochrome oxidase 1 gene. The geographic distribution of the different members of the complex was then compared with the incidence of CLCuD. RESULTS Using the Dinsdale nomenclature, the results revealed three putative species, Asia 1, Asia II 1 and Middle East-Asia Minor 1. Asia II 1 (also referred to in the literature as biotypes K, P, PCG-1, PK1, SY and ZHJ2) was only recorded from Punjab cotton plants, whereas Asia 1 (also referred to in the literature as biotypes H, M, NA and PCG-2) was found in both Sindh and Punjab. Middle East-Asia Minor 1 (commonly known as biotype B and B2) was found only in Sindh. Moreover, Asia II 1 was associated with high incidences of CLCuD, whereas regions where Middle East-Asia Minor 1 was present had a lower incidence. Phylogenetic analysis showed that the Middle East-Asia Minor 1 population in Sindh formed a distinct genetic subgroup within the putative species, suggesting that the Sindh province of Pakistan may form part of its home range. So far, no individuals from the putative species Mediterranean (commonly known as biotypes Q, J and L) have been found in Pakistan. CONCLUSIONS The capacity to manage pests and disease effectively relies on knowledge of the identity of the agents causing the damage. In the case of CLCuD in Pakistan, this knowledge has been obscured to some extent because of the inconsistent approach to identifying and distinguishing the different B. tabaci associated with CLCuD. The situation has now been clarified, and a strong association between disease incidence and vector identity and abundance has been shown. Given this advance, future research can now focus on factors that influence the capacity of different vector species to transmit the viruses that cause CLCuD, the reason for differences in vector abundance and the lack of geographic overlap between the cryptic vector species. This knowledge will contribute to the development of improved methods with which to manage the disease in Pakistan.
MAD Gates—Memristor Logic Design Using Driver Circuitry

Memristors have recently begun to be explored in arithmetic applications. However, all prior designs for memristor-based gates have had shortcomings in terms of scalability, applicability, completeness, and performance. In this brief, a new low-power gate design, i.e., memristors-as-drivers gates, is proposed, which overcomes each of these issues by combining sense circuitry with the IMPLY operation. By sensing the values of the input memristors as the driver for the output memristor, the delay is reduced to a single step for any Boolean operation, including <sc>xor</sc>. The area is reduced to at most three memristors for each gate and consumes only 30 fJ. An <inline-formula><tex-math notation="LaTeX">${N}$</tex-math></inline-formula>-bit ripple carry adder implementation is proposed, which uses these gates to achieve a total delay of <inline-formula><tex-math notation="LaTeX">${N}+1$</tex-math></inline-formula> with an area of 8<inline-formula><tex-math notation="LaTeX">${N}$</tex-math></inline-formula> memristors and their drivers. The individual bits of the proposed adder can be also pipelined, reducing the latency to four steps per addition.
Rapid Antidepressant Response with Ketamine: Is it the Solution to Resistant Depression?

Background: Treatment-resistant depression (TRD) is a relatively common condition, challenging the clinician. There is an urgent need to develop pharmacological treatments for TRD that exert rapid and sustained antidepressant effects. Ketamine induces a rapid antidepressant effect. Aims: In India, very few studies have corroborated such findings, and the present study aimed to assess the effectiveness and sustainability of antidepressant effects of ketamine in subjects with TRD. Materials and Methods: The present study was a single-center, prospective, 4-week, open-label, single-arm pilot study. Twenty-two subjects with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition major depression (treatment resistant) were recruited. After a 2-week drug-free period, subjects were given a single intravenous infusion of ketamine hydrochloride (0.5 mg/kg) and were rated at baseline and at 40, 80, 110, and 230 min and 1, 2, 3, 4, 7, and 14 days postinfusion. The main outcome measure was changes in scores on the 17-item Hamilton Depression Rating Scale (HDRS). Data were analyzed by using Freidman's analysis of variance and a post hoc test. Results: The ketamine infusion was effective in reducing the HDRS scores, and the change remained significant from minute 80 to day 3 postinfusion at each time point. The change was not significant at any time after day 3. Conclusion: The real strength of this study rests in documenting the rapid, albeit short-lived, antidepressant effect of ketamine in TRD.
Improving Quality of Hierarchical Clustering for Large Data Series

Brown clustering is a hard, hierarchical, bottom-up clustering of words in a vocabulary. Words are assigned to clusters based on their usage pattern in a given corpus. The resulting clusters and hierarchical structure can be used in constructing class-based language models and for generating features to be used in NLP tasks. Because of its high computational cost, the most-used version of Brown clustering is a greedy algorithm that uses a window to restrict its search space. Like other clustering algorithms, Brown clustering finds a sub-optimal, but nonetheless effective, mapping of words to clusters. Because of its ability to produce high-quality, human-understandable cluster, Brown clustering has seen high uptake the NLP research community where it is used in the preprocessing and feature generation steps. Little research has been done towards improving the quality of Brown clusters, despite the greedy and heuristic nature of the algorithm. The approaches tried so far have focused on: studying the effect of the initialisation in a similar algorithm; tuning the parameters used to define the desired number of clusters and the behaviour of the algorithm; and including a separate parameter to differentiate the window from the desired number of clusters. However, some of these approaches have not yielded significant improvements in cluster quality. In this thesis, a close analysis of the Brown algorithm is provided, revealing important under-specifications and weaknesses in the original algorithm. These have serious effects on cluster quality and reproducibility of research using Brown clustering. In the second part of the thesis, two modifications are proposed. Finally, a thorough evaluation is performed, considering both the optimization criterion of Brown clustering and the performance of the resulting class-based language models.
The burden of rare cancers in the United States

There are limited published data on the burden of rare cancers in the United States. By using data from the North American Association of Central Cancer Registries and the Surveillance, Epidemiology, and End Results program, the authors provide information on incidence rates, stage at diagnosis, and survival for more than 100 rare cancers (defined as an incidence of fewer than 6 cases per 100,000 individuals per year) in the United States. Overall, approximately 20% of patients with cancer in the United States are diagnosed with a rare cancer. Rare cancers make up a larger proportion of cancers diagnosed in Hispanic (24%) and Asian/Pacific Islander (22%) patients compared with non‐Hispanic blacks (20%) and non‐Hispanic whites (19%). More than two‐thirds (71%) of cancers occurring in children and adolescents are rare cancers compared with less than 20% of cancers diagnosed in patients aged 65 years and older. Among solid tumors, 59% of rare cancers are diagnosed at regional or distant stages compared with 45% of common cancers. In part because of this stage distribution, 5‐year relative survival is poorer for patients with a rare cancer compared with those diagnosed with a common cancer among both males (55% vs 75%) and females (60% vs 74%). However, 5‐year relative survival is substantially higher for children and adolescents diagnosed with a rare cancer (82%) than for adults (46% for ages 65‐79 years). Continued efforts are needed to develop interventions for prevention, early detection, and treatment to reduce the burden of rare cancers. Such discoveries can often advance knowledge for all cancers. CA Cancer J Clin 2017. © 2017 American Cancer Society. CA Cancer J Clin 2017;67:261–272. © 2017 American Cancer Society.
Scans as Primitive Parallel Operations Acknowledgement of Financial Support

In most parallel random-access machine (P-RAM) models, memory references are assumed to take unit time. In practice, and in theory, certain scan operations, also known as pre x computations, can executed in no more time than these parallel memory references. This paper outline an extensive study of the e ect of including in the P-RAM models, such scan operations as unit-time primitives. The study concludes that the primitives improve the asymptotic running time of many algorithms by an O(lgn) factor, greatly simplify the description of many algorithms, and are signi cantly easier to implement than memory references. We therefore argue that the algorithm designer should feel free to use these operations as if they were as cheap as a memory reference. This paper describes ve algorithms that clearly illustrate how the scan primitives can be used in algorithm design: a radix-sort algorithm, a quicksort algorithm, a minimumspanning-tree algorithm, a line-drawing algorithm and a merging algorithm. These all run on an EREW P-RAM with the addition of two scan primitives, and are either simpler or more e cient than their pure P-RAM counterparts. The scan primitives have been implemented in microcode on the Connection Machine System, are available in PARIS (the parallel instruction set of the machine), and are used in a large number of applications. All ve algorithms have been tested, and the radix-sort is the currently supported sorting algorithm for the Connection Machine. 2 Acknowledgement of Financial Support This report describes research done within the Arti cial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory's arti cial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under the O ce of Naval Research contract N00014{85{K{0124.
Molecular perception of interactions between bis(7)tacrine and cystamine-tacrine dimer with cholinesterases as the promising proposed agents for the treatment of Alzheimer’s disease

The infamous chronic neurodegenerative disease, Alzheimer’s, that starts with short-term memory loss and eventually leads to gradual bodily function decline which has been attributed to the deficiency in brain neurotransmitters, acetylcholine, and butylcholine. As a matter of fact, design of compounds that can inhibit cholinesterases activities (acetylcholinesterase and butylcholinesterase) has been introduced as an efficient method to treat Alzheimer’s. Among proposed compounds, bis(7)tacrine (B7T) is recognized as a noteworthy suppressor for Alzheimer’s disease. Recently a new analog of B7T, cystamine-tacrine dimer is offered as an agent to detain Alzheimer’s complications, even better than the parent compound. In this study, classical molecular dynamic simulations have been employed to take a closer look into the modes of interactions between the mentioned ligands and both cholinesterase enzymes. According to our obtained results, the structural differences in the target enzymes active sites result in different modes of interactions and inhibition potencies of the ligands against both enzymes. The obtained information can help to investigate those favorable fragments in the studied ligands skeletons that have raised the potency of the analog in comparison with the parent compound to design more potent multi target ligands to heal Alzheimer’s disease.
Marked differences in gustatory and gastrointestinal sensitivity to oleic acid between lean and obese men.

BACKGROUND Both orosensory stimulation and feedback from the gastrointestinal tract contribute to energy intake regulation. OBJECTIVE We evaluated the hypothesis that overweight or obese subjects would be less sensitive to both oral and intraduodenal oleic acid exposure than would lean subjects. DESIGN Eleven overweight or obese and 8 lean men were studied on 2 occasions, during which antropyloroduodenal pressures, plasma cholecystokinin and peptide YY, and appetite were measured during 90-min intraduodenal infusions of saline or oleic acid (18:1 load: 0.78 kcal/min); energy intake (buffet lunch) was determined immediately afterward. Oral detection thresholds for 18:1 and recent dietary intake (2-d recall) were also quantified. RESULTS In lean subjects, the number of isolated pyloric pressure waves (IPPWs) was greater during 18:1 infusion than during saline infusion (P < 0.05); no significant differences were observed between the 18:1 and saline infusions in the overweight or obese subjects. In both groups, 18:1 stimulated plasma cholecystokinin and peptide YY and suppressed energy intake compared with saline (P < 0.05), with trends for reduced cholecystokinin and energy intake responses in the overweight or obese subjects. Detection thresholds for 18:1 were greater in overweight or obese (7.9 ± 0.1 mmol/L) than in lean (4.1 ± 0.4 mmol/L) subjects (P < 0.05). Overweight or obese subjects had greater recent energy (P < 0.05) and fat (P = 0.07) intakes than did lean subjects. There was a direct relation (r = 0.669) of body mass index with 18:1 detection thresholds and inverse relations (r < -0.51) of IPPWs with body mass index and 18:1 detection thresholds (P < 0.05). CONCLUSIONS The ability to detect oleic acid both orally and within the gastrointestinal tract is compromised in obese men, and oral and gastrointestinal responses to oleic acid are related. This trial was registered at www.actr. org.au (Australian New Zealand Clinical Trials Registry) as 12609000557235.
The Effects of Distance Education on K-12 Student Outcomes: A Meta-Analysis.

4 Introduction 5 Distance Education in the K–12 Context 5 Characteristics for Success 6 Teaching and Learning Theory 7 Purpose of the Study 8 Method 10 Location and Selection of Studies 11 Limitations of the Review 13 Coding of Study Features 13 Calculation of Effect Sizes 14 Statistical Analysis of Effect Sizes 15 Results 15 Characteristics of the Study 15 Overall Effects on K–12 Distance Education 16 Publication and Methodological Variables 18 Distance Education Variables 18 Instructional and Program Variables 19 Discussion 19 Implications for Research and Practice 19 Conclusions 21 The Need for Prospective Study in Virtual Schooling 22 Recommendations for K–12 Online Learning Policy and Practice 23 References 26 Appendix: Coded Variables and Study Features in the Codebook 32
Design of adaptive and reliable mobile agent communication protocols

This paper presents a mailbox-based scheme for designing flexible and adaptive message delivery protocols in mobile agent (MA) systems. The scheme associates each mobile agent with a mailbox while allowing the decoupling between them, i.e., a mobile agent can migrate to a new site without bringing its mailbox. By separating the concerns of locating the mailbox of a mobile agent and delivering a message to the agent, we obtain a large space of protocol design with flexibility. Using a three-dimensional model based on the scheme, we have developed a taxonomy of MA communication protocols, which not only covers, as special cases, several known MA message delivery protocols, but also allows for the design of new ones well suited for various application requirements. We describe such an efficient and adaptive protocol derived front the model. The protocol guarantees reliable delivery of messages to mobile agents. We analyze the design trade-offs and performance of the protocol, using an analytic model as well as extensive simulation experiments.