Miracle-dz/UniFAR-FTUs huggingface dataset:
Paclitaxel/oxaliplatin/fluorouracil (TOF) regimen versus S-1/oxaliplatin (SOX) regimen for metastatic gastric cancer patients

Aims and background This study was designed to compare the efficacy and safety of paclitaxel/oxaliplatin/fluorouracil (TOF) regimen and S-1/oxaliplatin (SOX) regimen for metastatic gastric cancer (GC) patients. Methods Sixty patients were divided into TOF group and SOX groups randomly. Patients in the TOF group received paclitaxel (135 mg/m2 iv) on day 1, oxaliplatin (100 mg/m2 iv) on day 1, fluorouracil (500 mg/m2 continuous iv) on day 1-5. The patients in the SOX group received oxaliplatin (130 mg/m2 iv) on day 1 and S-1 (40 mg~60mg orally twice/day based on body surface area) on days 1-14. All the treatments were repeated every 21d for 4-6 cycles. Results The ORR and DCR of TOF group was 43.3% and 60.0%, respectively while that of SOX group was 36.7% and 56.7%. There were no statistical differences between the ORRs (? 2 = 0.278) and the DCRs (? 2 = 0.069) of the 2 groups. The majority of adverse events of two groups were hematological and digestive ones. Most of them were grade I and II. The adverse event rate of TOF group was higher than SOX group. The PFS times of TOF and SOX groups were 6.5 and 5.8 months, respectively. There was no statistical difference between the PFSs of the 2 groups (P = 0.451). Conclusions The efficacies of TOF and SOX regimens are similar but the safety of SOX regimen better than TOF regimen.
Isolation by distance under diverse systems of mating.

HE effects of restricted dispersion on the genetic properties of a continuous T population have been treated mathematically in a previous paper (WRIGHT 1943a). The conclusions have been applied to the interpretation of observed local variability in a population of a plant, Linanthus Parryi (WRIGHT 1943b) and in one of an animal, Drosophila pseudoobscura (DOBZHANSKY and WRIGHT 1943). The mathematical treatment was based on the assumption of completely random union of gametes within each neighborhood and thus would rarely be strictly applicable to actual cases. The purposes of the present paper are to compare the effects of various systems of mating within continuous populations, and to present a more accurate method than before for estimating from data an important theoretical quantity, N, the effective size of population of a “neighborhood” in the sense discussed below. It was postulated in the previous paper that a population of uniform density occupies either an indefinitely large area (area continuity) or a strip of indefinitely great length but of such narrow width that dispersion occurs across it within a single generation (linear continuity). Both uniparental and biparental reproduction were considered. In the former case, it was postulated that the locations of parents a t some phase of the life cycle are distributed, relative to the corresponding locations of their progeny, according to a normal probability curve with a standard deviation U, if there is linear continuity, or in a bivariate normal distribution with standard deviation u, for both x and y coordinates of the parental locations (relative to their progeny) if there is area continuity. I n the case of biparental reproduction the locations of the parents were assumed to be uncorrelated with each other. This is assumed to hold in the present paper except as qualified by self fertilization or brother-sister mating in excess of random. A term is needed to designate the local population of which the parents may be considered as representative. Various terms were used in the preceding paper. (‘Panmictic unit” applies only if there is completely random mating locally and is thus not sufficiently general. “Parental group” is better but is somewhat awkward. An essential property of the population in question is that the individuals are neighbors in the sense that their gametes may come together. The term “neighborhood” is thus an appropriate one for this important unit.
A Survey on the Present State-of-the-Art of Explosives, Detection Methods and Automatic Explosive Detection using Wireless Sensor Network

Though the There is ever increasing evidence of increased terrorist activities that spread entire world. In the wake of modern technologies and diversified threats, it is indispensable to comprehend, detect and prevent with reliable countermeasures. In this context detection of explosives is an active research area. Towards this end many detection systems came into existence. The government agencies in various countries are equipped with the devices that can detect explosives. However, often they are bulky in nature and they are publicly visible and expensive. Therefore it is not feasible to use them in the present condition in public places such as railway stations, airports, bus stations and so on. Manual intervention is another problem in the traditional systems. Therefore there is immediate need for the detection of explosives to be incorporated in a mobile network like Wireless Sensor Network (WSN). Since the nodes of WSN can be deployed hidden from public view, such network is an ideal candidate to have real time and automated detection of explosives. The realization of such networks can pave the way for installation at public domains to safeguard lives and property of citizens. Towards this end we review the literature on the present state-of-the-art of explosives, their characterization, detection methods including the usage of Wireless Sensor Networks (WSNs) for automatic and real time explosive detection. This paper gives insights into different insights into explosives and detection methods that can help in further research towards realizing a fool proof system for explosive detection.
Severe Hypoinsulinaemic Hypoglycaemia in a Premature Infant Associated with Poor Weight Gain and Reduced Adipose Tissue

Background: Hypoglycaemia is common in preterm and intrauterine growth retarded (IUGR) newborns. Although preterm and IUGR infants have limited adipose tissue stores, the role of adipose tissue and the associated adipocytokines in glucose physiology is not known. Aim: We report the case of a premature intrauterine growth retarded infant who had poor weight gain for the first 6 weeks of life and then developed severe hypoinsulinaemic hypoketotic hypoglycaemia. Results: There was markedly reduced adiposity with low serum leptin and adiponectin levels. Total energy expenditure and body composition measurements showed that body fat as a percentage of weight averaged 7% at 20 weeks and 28% at 28 weeks. At 20 weeks of age, the patient was equivalent to a deficit of >2 SD scores of body fat, but average fatness by 28 weeks. The hypoglycaemia completely resolved when the patient started gaining weight with an increase in fat mass and a concomitant increase in serum leptin and adiponectin level. Conclusions: Although the precise mechanism of this patient’s severe hypoglycaemia is unclear, further studies are required to understand the role of adipose tissue and adipocytokines in glucose homeostasis in preterm and IUGR infants.
Effective path selection for delay fault testing of sequential circuits

This paper outlines several problems related to the delay fault testing of sequential circuits. For timing test of a circuit and for layout optimization, critical path data are needed. When critical paths are identified by a static timing analyzer many of the selected paths cannot be activated functionally. Such paths are sequential false paths. However, many of these paths can be activated and tested in the full or partial scan mode due to the increased controllability and observability. Therefore, it is possible that detection of a timing error on a sequential false path, when scan mode is used, can lead to the rejection of a functionally good circuit. We propose that these paths should not be targeted during delay test if scan mode is used. Similarly, sequential false paths should not be used for layout optimization or for selection of maximum clock rate. We present a novel algorithm to identify these paths. This algorithm is based on functional analysis of each target path for single and multiple path activation. If a path cannot be activated either way, it is sequentially false.
Parsing Expression Grammars with Unordered Choices

Parsing expression grammars (PEGs) were formalized by Ford in 2004, and have several pragmatic operators (such as ordered choice and unlimited lookahead) for better expressing modern programming language syntax. In addition, PEGs can be parsed in a linear time by using recursive-descent parsing and memoization. In this way, PEGs have a lot of positive aspects. On the other hand, it is known that ordered choices defy intuition. They may cause bugs. This is due to a priority of an ordered choice. To avoid this, unordered choices are required. In this paper, we define a parsing expression grammar with unordered choices (PEGwUC), an extension of a PEG with unordered choices. By the extension, it is expected that a PEGwUC includes both a PEG and a context-free grammar (CFG), and this allows us to write a grammar more intuitively. Furthermore, we show an algorithm for parsing a PEGwUC. The algorithm runs in a linear time when a PEGwUC does not include unordered choice and in a cubic time in worst-case running time.
Global vs local classification models for multi-sensor data fusion

The aim of this paper is to investigate feature extraction and fusion of information across a number of sensors in different spatial locations to classify temporal events. Although the common feature-level fusion allows capturing spatial dependencies across sensors, the significant increase of feature vector dimensionality does not allow learning the classification models using a small number of samples usually available in practice. In decision-level fusion on the other hand, sensor-specific classification models are trained and subsequently integrated to reach a combined decision. Recent work has shown that decision-level fusion with a global (common for all sensors) classification model, is more appropriate for generalized events that show a (weak or strong) manifestation across all sensors. Although we can hypothesize that the choice of scheme depends on the event type (generalized vs focal/local), the prior work does not provide enough evidence to guide on the choice of fusion scheme. Thus in this work we aim to compare the three data fusion schemes for classification of generalized and non-generalized events using two case scenarios: (i) classification of paroxysmal events based on EEG patterns and (ii) classification of falls and activities of daily living (ADLs) from multiple sensors. The results support our hypothesis that feature level fusion is more beneficial for the characterization of heterogeneous data (based on an adequate number of samples), while sensor-independent classifiers should be selected in the case of generalized manifestation patterns.
Importance of Perceived Brand Ranking for B2B Customers in Making High Risk Purchasing Decision

Brand Building and Brand promotions are undoubtedly means of generating large revenues in today’s B2B industrial market. However, due to globalization and access to multiple information data base, the organizations with equal brand equities and brand image exists in the Industrial segments. Therefore, it become extremely difficult for the Buying Center in B2B segment to arrive quickly on the purchasing decision. Therefore, in today’s intense marketing era, a deliberate attempt is needed to improve the perceived Brand Ranking in the minds of buying center. Strong brand ranking thus has become a very important factor that influences customer perceptions of a brand. In the success of Brand Management, Brand ranking is gaining significant importance alongwith brand equity from understanding and managing them correctly. Today’s marketing professionals need to pay deliberate attention to Brand ranking so as to produce strong attributes that will influence customers when making their choices.This research paper focuses on the importance brand ranking and how it is being perceived by B2B customers while making purchasing decision. This is based on the assumption that the other dimensions such as brand promotions, brand equity are at the same level and the customers knowingly and unknowingly makes a comparison based on the rank of the brand.However, this research paper aims to find out if the perceived financial and business risks in the minds of the members of buying center significantly impacts the perceived Brand Ranking. Brand awareness was treated separately from other dimensions because of the difference in scale.A structured questionnaire was constructed to provide answers to our research question. In this study, one hundred questionnaires were distributed, but only eightytwo questionnaires were received out of which seventy six has been realized. The study surveyed four dimensions of perceived risk, value proposition, brand Imageand brand ranking of two top brands in lubricants. Among these dimensions, brand image appears to have the least brand ranking rating by consumers than the other dimensions. However, all these dimensions more or less influence the perceived brand ranking by the customer.
The effect of load modelling on phase balancing in distribution networks using search harmony algorithm

Due to the unequal loads in phases and different customer consumption, the distribution network is unbalanced. Unbalancing in the distribution network, in addition to increasing power losses, causes unbalancing in voltages and increases operating costs. To reduce this unbalancing, various methods and algorithms have been presented. In most studies and even practical projects due to lack of information about the network loads, load models such as constant power model, constant current or constant impedance are used to model the loads. Due to the changing and nonlinear behaviours of today's loads, these models cannot show results in accordance with reality. This paper while introducing an optimal phase-balancing method, discusses the effect of load modelling on phase balancing studies. In this process the re-phasing method for balancing the network and the harmony search algorithm for optimizing the phase displacement process have been used. The simulation was carried out on an unbalanced distribution network of 25 buses. The results show well the effect of this comprehensive modelling on phase balancing studies. It also shows that in the re-phasing method for balancing the network and in the absence of a real load model, the use of which model offers the closest answer to optimal solutions.
A Mistaken Diagnosis of Secondary Glioblastoma as Parasitosis

Background: Glioblastoma is a malignant brain tumor with poor prognosis requiring early diagnosis. Secondary glioblastoma refers to cases that progressed from low-grade glioma. Evidence shows that timely resection correlates with increased survival. Case presentation: We describe a case of a patient with secondary glioblastoma who was mistakenly diagnosed with Angiostrongylus cantonensis infection until 7 years after disease onset. The patient presented with non-specific clinical manifestations at disease onset. A conventional magnetic resonance imaging (MRI) in the primary survey provided insufficient information, and thus failed to identify the malignancy. During follow-up, unfortunately, clinicians were misled by the patient's raw food diet, a positive serum parasite antibody and a result of low glucose metabolism on Fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET-CT). The patient was diagnosed with parasitosis. However, his condition kept getting worse under antiparasitic treatment. Preoperative magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) failed to reverse the mistaken impression. Final diagnosis was confirmed until intraoperative and postoperative pathological findings indicated glioblastoma. Conclusion: We ascribe the incorrect diagnosis to insufficient understanding on imaging manifestations of brain neoplasm as well as clinical features of parasitosis. Thus, we review the MRI, FDG-PET-CT, MRS, and DTI data of this case according to the timeline, refer to relevant studies, and point out the pitfalls. With a long course of slowly progressing, this was a rare case of secondary glioblastoma with the absence of isocitrate dehydrogenase 1 (IDH1) gene mutation.
Design Ideation with Cooperative Contextual Bandits

Design ideation is a prime creative activity in design. However, it is challenging to support computationally due to its quickly evolving and exploratory nature. The paper presents cooperative contextual bandits (CCB) as a machine-learning method for interactive ideation support. A CCB can learn to propose domain-relevant contributions and adapt their exploration/exploitation strategy. We developed a CCB for an interactive design ideation tool that 1) suggests inspirational and situationally relevant materials (“may AI? ”); 2) explores and exploits inspirational materials with the designer; and 3) explains its suggestions to aid reflection. The application case of digital mood board design is presented, wherein visual inspirational materials are collected and curated in collages. In a controlled study, 14 of 16 professional designers preferred the CCB-augmented tool. The CCB approach holds promise for ideation activities wherein adaptive and steerable support is welcome but designers must retain full outcome control.
A Unification of Edmonds ’ Routing Theorem and Ahlswede et al ’ s Network Coding Theorem

Given a network of lossless links with rate constraints, a source node, and a set of destination nodes, the multicast capacity is the maximum rate that the source can transmit common information to the destinations. The multicast capacity cannot exceed the capacity of any cut separating the source from a destination. The minimum of the cut capacities is called the cut bound. A fundamental graph theory by Edmonds established that if all nodes other than the source are destinations, the cut bound can be achieved by routing. In general, however, the cut bound cannot be achieved by routing. Ahlswede et al. established that the cut bound can be achieved by performing network coding, which generalizes routing by allowing information to be mixed. This paper presents a unifying theory, which has Edmonds’ Routing Theorem and Ahlswede et al.’s Network Coding Theorem as special cases. Specifically, it shows that the multicast capacity can still be achieved even though information mixing is only allowed on edges entering relay nodes.
Robust and energy efficient trajectories for robots in a common workspace setting

Abstract A method, incorporating robustness into trajectory planning, is proposed in this article. In the presence of delays, the suggested approach guarantees collision-free scenarios for robots with predefined paths and overlapping workspaces. Traditionally, only the time at which a robot can enter a common workspace is constrained so as to avoid collisions. If the shared zone becomes available later than planned, collisions can potentially occur if the robot is unable to stop before entering the shared space. In this work, a clearance point is introduced where the occupancy of the common workspace is evaluated. The velocity is constrained at this point such that, if necessary, the robot is able to stop at the boundary of the shared space. The closer to the boundary the evaluation is performed, the more restricted is the velocity. The problem formulation is stated in space assuming a predefined path, where robot dynamics and robust constraints are included. Multiple objectives corresponding to final time and energy consumption are considered. The impact on the system performance concerning the position and timing related to the clearance point is analyzed. An example is presented, where the optimal clearance point position is determined, based on the time at which the shared space is assumed to become available.
MISCONCEPTIONS: BICARBONATE AS AN ERGOGENIC AID? A PHYSICAL, CHEMICAL, MECHANISTIC VIEWPOINT.

KAY, B. Misconceptions: Bicarbonate as an ergogenic aid? A physical, chemical, mechanistic viewpoint. Brazilian Journal of Biomotricity, v. 2, n. 4, p. 205-219, 2008. The ergogenic effect of sodium bicarbonate has been extensively studied. Results have been equivocal. Bicarbonate (HCO3 - ) is widely proposed as having a possible ergogenic effect via an attenuation of exercise induced acidification, and / or via increased rapidity of lactate export from working muscles. Lactate is cited as being co-exported with protons, in a 1:1 stoichiometry. With respect to the model proposing bicarbonate as an ergogenic aid: (a) exercise induced acidosis may not be deleterious to exercise performance; (b) both [HCO3 - ] and [H + ] are dependant variables and therefore unable to be primarily or independently moderated; (c) The finding that ingestion / infusion of NaHCO3 results in increased lactate export rate from working muscles is not universal (d) whether or not protons are co-exported from muscle cells with lactate is irrelevant to [H
Unsupervised Semantic Approach of Aspect-Based Sentiment Analysis for Large-Scale User Reviews

Aspect-based sentiment analysis (ABSA) has recently attracted increasing attention due to its extensive applications. Most of the existing ABSA methods been applied on small-sized labeled datasets. However, real datasets such as the Amazon and TripAdvisor contain a massive number of reviews. Thus, applying these methods on large-scale datasets may produce inefficient results. Furthermore, these existing methods extract huge number of aspects, most of which are not relevant to the domain of interest. But, on other hand, some of the infrequent relevant aspects are excluded during the extraction process. These limitations negatively affect the performance of the ABSA process. This article, therefore, aims to overcome such limitations by proposing an efficient approach that is suitable for real large-scale unlabeled datasets. The proposed approach is a combination of hybridizing a frequency-based approach (word level) and a syntactic-relation based approach (sentence level). It was enhanced further with a semantic similarity-based approach to extract aspects that are relevant to the domain, even terms (related to the aspects) are not frequently mentioned in the reviews. The extracted aspects according to the proposed approach are used to generate a total review sentiment score after estimating the weight and the rating of each extracted aspect mentioned in the review. The assignment of the weight of each extracted aspect is calculated based on a modified TF-IDF weighting scheme and the assignment of the aspect rating is calculated based on a domain-specific lexicon. Effectiveness of the extracted aspects is evaluated against two baselines available from existing literature: fixed aspect and extracted aspects. Evaluation was also performed by using a general lexicon and a domain-specific lexicon. Results in terms of F-measure and accuracy on Amazon and Yelp datasets show that the extracted aspects using the proposed approach with the domain-specific lexicon outperformed all the baselines.