LLukas22/scidocs huggingface dataset:
Quantum Programming Languages: Survey and Bibliography

The emphasis is made on the juxtaposition of (quantum theorem) proving versus quantum (theorem proving). The logical contents of verification of the statements concerning quantum systems is outlined. The Zittereingang (trembling input) principle is introduced to enhance the resolution of predicate satisfiability problem provided the processor is in a position to perform operations with continuous input. A realization of Zittereingang machine by a quantum system is suggested. Introduction What is the desirable way to broaden the facilities of processors in order to have progress in solving NP-hard problems? The principle of trembling input I am going to put forth in this paper will require a flexibility of processor. That means that it will be assumed that the processor is able to deal with ”intermediate outputs”, or, in other words, that it will be possible to pass continuously from one input to another. We shall also assume that all possible inputs form a linear space, and that the result depends contiuously on input preserving linear combinations. To elucidate the idea of the principle I suggest to consider the SAT problem. Suppose that, solving some problem, you succeded to reduce it to the following one: given a propositional form P (x1, . . . , xn) of,
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomic knowledge, ATOMIC focuses on inferential knowledge organized as typed if-then relations with variables (e.g., “if X pays Y a compliment, then Y will likely return the compliment”). We propose nine if-then relation types to distinguish causes vs. effects, agents vs. themes, voluntary vs. involuntary events, and actions vs. mental states. By generatively training on the rich inferential knowledge described in ATOMIC, we show that neural models can acquire simple commonsense capabilities and reason about previously unseen events. Experimental results demonstrate that multitask models that incorporate the hierarchical structure of if-then relation types lead to more accurate inference compared to models trained in isolation, as measured by both automatic and human evaluation. Introduction Given a snapshot observation of an event, people can easily anticipate and reason about unobserved causes and effects in relation to the observed event: what might have happened just before, what might happen next as a result, and how different events are chained through causes and effects. For instance, if we observe an event “X repels Y’s attack” (Figure 1), we can immediately infer various plausible facts surrounding that event. In terms of the plausible motivations behind the event, X probably wants to protect herself. As for the plausible pre-conditions prior to the event, X may have been trained in self-defense to successfully fend off Y’s attack. We can also infer the plausible characteristics of X; she might be strong, skilled, and brave. As a result of the event, X probably feels angry and might want to file a police report. Y, on the other hand, might feel scared of getting caught and want to run away. The examples above illustrate how day-to-day commonsense reasoning can be operationalized through a densely connected collection of inferential knowledge. It is through this knowledge that we can watch a two-hour movie and understand a story that spans over several months, as we can reason about a great number of events, causes, and effects, Copyright c © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. X repels Y's attack X wanted to save themselves X wanted to protect others Y wants to run home X wants to file a police report X wants to leave the scene X needs to know self-defense X is skilled as a result, X wants
Reliability of the Spinal Instability Neoplastic Score (SINS) among radiation oncologists: an assessment of instability secondary to spinal metastases

BACKGROUND
The Spinal Instability Neoplastic Score (SINS) categorizes tumor related spinal instability. It has the potential to streamline the referral of patients with established or potential spinal instability to a spine surgeon. This study aims to define the inter- and intra-observer reliability and validity of SINS among radiation oncologists.


METHODS
Thirty-three radiation oncologists, across ten international sites, rated 30 neoplastic spinal disease cases. For each case, the total SINS (0-18 points), three clinical categories (stable: 0-6 points, potentially unstable: 7-12 points, and unstable: 13-18 points), and a binary scale ('stable': 0-6 points and 'current or possible instability'; surgical consultation recommended: 7-18 points) were recorded. Evaluation was repeated 6-8 weeks later. Inter-observer agreement and intra-observer reproducibility were calculated by means of the kappa statistic and translated into levels of agreement (slight, fair, moderate, substantial, and excellent). Validity was determined by comparing the ratings against a spinal surgeon's consensus standard.


RESULTS
Radiation oncologists demonstrated substantial (κ=0.76) inter-observer and excellent (κ=0.80) intra-observer reliability when using the SINS binary scale ('stable' versus 'current or possible instability'). Validity of the binary scale was also excellent (κ=0.85) compared with the gold standard. None of the unstable cases was rated as stable by the radiation oncologists ensuring all were appropriately recommended for surgical consultation.


CONCLUSIONS
Among radiation oncologists SINS is a highly reliable, reproducible, and valid assessment tool to address a key question in tumor related spinal disease: Is the spine 'stable' or is there 'current or possible instability' that warrants surgical assessment?
Assessment of personality dimensions in children and adolescents with bipolar disorder using the Junior Temperament and Character Inventory.

OBJECTIVE
We compared temperament and character traits in children and adolescents with bipolar disorder (BP) and healthy control (HC) subjects.


METHOD
Sixty nine subjects (38 BP and 31 HC), 8-17 years old, were assessed with the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime. Temperament and character traits were measured with parent and child versions of the Junior Temperament and Character Inventory.


RESULTS
BP subjects scored higher on novelty seeking, harm avoidance, and fantasy subscales, and lower on reward dependence, persistence, self-directedness, and cooperativeness compared to HC (all p < 0.007), by child and parent reports. These findings were consistent in both children and adolescents. Higher parent-rated novelty seeking, lower self-directedness, and lower cooperativeness were associated with co-morbid attention-deficit/hyperactivity disorder (ADHD). Lower parent-rated reward dependence was associated with co-morbid conduct disorder, and higher child-rated persistence was associated with co-morbid anxiety.


CONCLUSIONS
These findings support previous reports of differences in temperament in BP children and adolescents and may assist in a greater understating of BP children and adolescents beyond mood symptomatology.
Protective Effects of Ginger against Aspirin-Induced Gastric Ulcers in
Rats

We investigated the mechanism underlying the protective effects of ginger against gastric damage induced by aspirin in rats. Gastric mucosal lesions were produced by orally administering 200 mg/kg aspirin suspended in 1% carboxymethylcellulose solution to pyloric-ligated male Wistar rats. Ginger powder (200 mg/kg) markedly reduced the aspirin-induced gastric hemorrhagic ulcer area. The total acidity of gastric juice was not significantly influenced by aspirin or ginger. Ginger powder did not affect the aspirin-induced reduction in mucosal prostaglandin E2 (PGE2) content; however, it did ameliorate the aspirin-induced increases in mucosal activity of the inducible form of NO synthase (iNOS) and plasma tumor necrosis factor (TNF)-α and interleukin (IL)-1β levels. In the next experiment, high and low doses of 6-gingerol and 6-shogaol were used instead of ginger powder in the same experimental model to examine their roles in the anti-ulcer mechanism of ginger. Both 6-gingerol and 6-shogaol reduced aspirin induced ulcer formation, mucosal iNOS and plasma TNF-α and IL-1β levels. In conclusion, ginger powder prevents the aspirin induced gastric ulcer formation by reducing mucosal iNOS activity and the plasma levels of inflammatory cytokines but does not affect gastric juice or acid production or mucosal PGE2 content. This protective effect of ginger powder against gastric ulcers may be attributable to both gingerol and shogaol.
Comparison of closing-wedge and opening-wedge high tibial osteotomy for medial compartment osteoarthritis of the knee: a randomized controlled trial with a six-year follow-up.

BACKGROUND
Varus deformity increases the risk of progression of medial compartment knee osteoarthritis. The aim of this study was to investigate the clinical and radiographic mid-term results of closing-wedge and opening-wedge high tibial osteotomy when used to treat this condition.


METHODS
From January 2001 to April 2004, ninety-two patients were randomized to receive either a closing-wedge or an opening-wedge high tibial osteotomy. The clinical outcome and radiographic results were examined preoperatively; at one year; and, for the present study, at six years postoperatively. The outcomes that we reviewed included maintenance of the achieved correction, progression of osteoarthritis (based on the Kellgren and Lawrence classification), severity of pain (as assessed on a visual analog scale [VAS]), knee function (as measured with the Hospital for Special Surgery [HSS] score and Knee injury and Osteoarthritis Outcome Score [KOOS]), walking distance, complications, and survival with conversion to a total knee arthroplasty as the end point. The results were analyzed on the basis of the intention-to-treat principle.


RESULTS
Six years postoperatively, the mean hip-knee-ankle (HKA) angle (and standard deviation) was 3.2° ± 4.1° of valgus after a closing-wedge high tibial osteotomy and 1.3° ± 5.0° of valgus after an opening-wedge high tibial osteotomy (p = 0.343). In both groups, the six-year postoperative HKA angles did not differ from the respective one-year postoperative angles. No difference in the severity of pain or in knee function was found between the two groups. Four complications (9%) occurred in the closing-wedge group and seventeen (38%), in the opening-wedge group. Ten (22%) of the patients in the closing-wedge group and three (8%) in the opening-wedge group needed conversion to a total knee arthroplasty within the six-year period (p = 0.05). The difference in the percentage of cases with conversion to total knee arthroplasty was 14% (95% confidence interval [CI] = 21.7 to 0.2).


CONCLUSIONS
In the group of patients without conversion to a total knee arthroplasty, there was no difference between the high tibial closing-wedge and opening-wedge osteotomies in terms of clinical outcomes or radiographic alignment at six years postoperatively. Opening-wedge osteotomy was associated with more complications, but closing-wedge osteotomy was associated with more early conversions to total knee arthroplasty.


LEVEL OF EVIDENCE
Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
Response of residential electricity demand to price: The effect of measurement error

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV is greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that a carbon tax or other pricebased policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants. JEL Classification: D, D2, Q, Q4, Q5.
Relevant data expansion for learning concept drift from sparsely labeled data

Keeping track of changing interests is a natural phenomenon as well as an interesting tracking problem because interests can emerge and diminish at different time frames. Being able to do so with a few feedback examples poses an even more important and challenging problem because existing concept drift learning algorithms that handle the task typically suffer from it. This work presents a new computational framework for extending incomplete labeled data stream (FEILDS), which extends the capability of existing algorithms for learning concept drift from a few labeled data. The system transforms the original input stream into a new stream that can be conveniently tracked by the existing learning algorithms. The experiment results reveal that FEILDS can significantly improve the performances of a Multiple Three-Descriptor Representation (MTDR) algorithm, Rocchio algorithm, and window-based concept drift learning algorithms when learning from a sparsely labeled data stream with respect to their performances without using FEILDS.
A Model for Learned Bloom Filters and Related Structures

Recent work has suggested enhancing Bloom filters by using a pre-filter, based on applying machine learning to model the data set the Bloom filter is meant to represent. Here we model such learned Bloom filters, clarifying what guarantees can and cannot be associated with such a structure.
Testing of a Wavelet-Packet-Transform-Based Differential Protection for Resistance-Grounded Three-Phase Transformers

This paper presents an extension of real-time tests of a wavelet-packet-transform-based technique for the differential protection of three-phase power transformers. The proposed technique is implemented using a DS1102 digital signal processor board and tested on two different three-phase power transformers with neutral resistance grounded. Different magnetizing inrush and internal fault currents are investigated with current transformer (CT) saturation for different loading conditions, including capacitive loads. The results show a complete independence from transformer parameters, load types, grounding method, or CT saturation. Furthermore, the proposed technique has high speed, good accuracy, small required memory, and reliable responses with reduced computational burden. In all cases of the investigated internal faults, the proposed algorithm is capable of identifying the fault and generating a trip signal in less than a quarter cycle based on a 60-Hz system.
Management of impending necrosis associated with soft tissue filler injections.

BACKGROUND
As the number of soft tissue filler injections increases, the number of adverse events associated with injection may rise. Impending necrosis represents a serious complication that, if not treated correctly and timely, may have grave consequences.


OBJECTIVE
We describe a protocol utilizing hyaluronidase, nitroglycerin paste, aspirin, antacid and a topical oxygen therapy that may be used to treat impending necrosis subsequent to injection with soft tissue fillers.


CONCLUSION
We have successfully treated nine post-filler injection adverse events involving impending necrosis or necrosis following both hyaluronic acid and calcium hydroxylapatite injections using our protocol.
Yoga’s effect on inflammatory biomarkers and metabolic risk factors in a high risk population – a controlled trial in primary care

BACKGROUND
Yoga can reduce blood pressure and has also been suggested to reduce inflammatory biomarkers and metabolic risk factors for cardiovascular diseases (CVDs). We aimed to assess the benefit of two yoga interventions on inflammatory biomarkers and metabolic risk factors in a high risk population in primary care.


METHODS
Adult patients from a health care center in Sweden, with diagnosed hypertension, were invited to undergo a baseline check at the health care center. Baseline check included standardized blood pressure measurement, BMI and weight circumference measurements, blood sampling (hs-CRP, IL-6, FP-glucose, HbA1c, cholesterol, TG, LDL and HDL) and a questionnaire on self-rated quality of life (WHOQOL-BREF). There were three groups: 1) yoga class with yoga instructor; 2) yoga at home; and 3) a control group. In total, 83 patients were included and matched at the group level for systolic blood pressure. A majority of the patients (92 %) were on antihypertensive medication, which they were requested not to change during the study. After 12 weeks of intervention, the assessments were performed again.


RESULTS
We recorded no evidence that yoga altered inflammatory biomarkers or metabolic risk factors in our study population. A total of 49 participants (59 %) met the criteria for metabolic syndrome.


CONCLUSION
The yoga interventions performed in our study did not affect inflammatory biomarkers or metabolic risk factors associated with CVD in the study population of primary care patients with hypertension. Further randomized trials are needed to elucidate the effects of yoga on CVD risk factors in this particular group.


TRAIL REGISTRATION
NCT01302535 , February 22, 2011.
Vitamin E and donepezil for the treatment of mild cognitive impairment.

BACKGROUND
Mild cognitive impairment is a transitional state between the cognitive changes of normal aging and early Alzheimer's disease.


METHODS
In a double-blind study, we evaluated subjects with the amnestic subtype of mild cognitive impairment. Subjects were randomly assigned to receive 2000 IU of vitamin E daily, 10 mg of donepezil daily, or placebo for three years. The primary outcome was clinically possible or probable Alzheimer's disease; secondary outcomes were cognition and function.


RESULTS
A total of 769 subjects were enrolled, and possible or probable Alzheimer's disease developed in 212. The overall rate of progression from mild cognitive impairment to Alzheimer's disease was 16 percent per year. As compared with the placebo group, there were no significant differences in the probability of progression to Alzheimer's disease in the vitamin E group (hazard ratio, 1.02; 95 percent confidence interval, 0.74 to 1.41; P=0.91) or the donepezil group (hazard ratio, 0.80; 95 percent confidence interval, 0.57 to 1.13; P=0.42) during the three years of treatment. Prespecified analyses of the treatment effects at 6-month intervals showed that as compared with the placebo group, the donepezil group had a reduced likelihood of progression to Alzheimer's disease during the first 12 months of the study (P=0.04), a finding supported by the secondary outcome measures. Among carriers of one or more apolipoprotein E epsilon4 alleles, the benefit of donepezil was evident throughout the three-year follow-up. There were no significant differences in the rate of progression to Alzheimer's disease between the vitamin E and placebo groups at any point, either among all patients or among apolipoprotein E epsilon4 carriers.


CONCLUSIONS
Vitamin E had no benefit in patients with mild cognitive impairment. Although donepezil therapy was associated with a lower rate of progression to Alzheimer's disease during the first 12 months of treatment, the rate of progression to Alzheimer's disease after three years was not lower among patients treated with donepezil than among those given placebo.
Low-Power Low-Rate Goes Long-Range: The Case for Secure and Cooperative Machine-to-Machine Communications

The vision of connecting a large amount of objects on this planet to improve well-being and safety is slowly taking shape. Preceded by a decade-long era of research on low-power low-rate shortrange wireless sensor networks, first proprietary and later standardscompliant embedded technologies have successfully been put forward. Cellular machine-to-machine (M2M) is taking this technology to a next step where communication ranges are significantly extended by relying on cellular infrastructure. This position paper discusses these emerging paradigms and highlights how cooperative as well as security requirements are core to their designs. 1 Introductory Remarks The world is becoming increasingly connected. Information and communications technologies (ICT) are a true facilitator of this connectivity. The revolution, which a few decades ago began to connect people by means of mobile phones, is slowly ebbing down as virtually every human being is “cellphoned” today. Similarly, the revolution, which a few decades ago began to connect computers via the (today) Internet, is also ebbing down as virtually every computer is essentially “interneted” today. Another revolution, however, has slowly began to take shape: the one of interconnecting objects around us and thereby allowing to create an Internet of Things (IoT) [1]. Not all objects will be connected, however; and the majority not even in short term. Objects important to the well being and safety of humans will likely be connected first, leading to the vision of Internet of Important Things (IoIT) and acting as physical extension of the current Internet. The myriad of applications is huge and the benefit well understood [2]. Connecting objects, devices, things is clearly an opportunity but also poses serious challenges. The opportunity is in instrumenting and interconnecting the physical world around us and thus allowing it to act intelligently; this is essentially the vision of IBM’s Smarter Planet initiative [3]. The main challenges remain in viably networking this large amount of objects given their obvious constraints in power, processing capabilities, memory and size.
A fuzzy logic-based text classification method for social media

A FUZZY LOGIC-BASED TEXT CLASSIFICATION METHOD FOR SOCIAL MEDIA
Adjunctive psychotherapy for bipolar disorder: effects of changing treatment modality.

In a randomized, controlled trial, the authors studied an adjunctive, individual psychotherapy, interpersonal and social rhythm therapy (IPSRT) for bipolar disorder. After stabilizing participants with episode appropriate pharmacotherapy and either IPSRT or intensive clinical management (CM), participants were reassigned to IPSRT or CM in conjunction with pharmacotherapy for 2 years of preventative treatment. Early results (n = 82) suggest that altering participants' treatment assignment at entry to the preventative phase is related to risk of recurrence. Participants remaining in the same treatment for both acute and preventative phases had lower rates of recurrence (< 20% vs. > 40%) and levels of symptomatology over the subsequent 52 weeks than those reassigned to the alternate modality. This finding, consistent with the authors' philosophy that bipolar patients benefit from stable routines, suggests that disruptions in the psychosocial treatment plan contribute to worse outcomes.