nils-herrmann/clean_scirepeval huggingface dataset:
The magical number 4 in short-term memory: a reconsideration of mental storage capacity.

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recording of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed.
Toward End-to-End Face Recognition Through Alignment Learning

A common practice in modern face recognition methods is to specifically align the face area based on the prior knowledge of human face structure before recognition feature extraction. The face alignment is usually implemented independently, causing difficulties in the designing of end-to-end face recognition models. We study the possibility of end-to-end face recognition through alignment learning in which neither prior knowledge on facial landmarks nor artificially defined geometric transformations are required. Only human identity clues are used for driving the automatic learning of appropriate geometric transformations for the face recognition task. Trained purely on publicly available datasets, our model achieves a verification accuracy of 99.33% on the LFW dataset, which is on par with state-of-the-art single model methods.
Citrus polyphenol hesperidin stimulates production of nitric oxide in endothelial cells while improving endothelial function and reducing inflammatory markers in patients with metabolic syndrome.

Hesperidin, a citrus flavonoid, and its metabolite hesperetin may have vascular actions relevant to their health benefits. Molecular and physiological mechanisms of hesperetin actions are unknown.



We tested whether hesperetin stimulates production of nitric oxide (NO) from vascular endothelium and evaluated endothelial function in subjects with metabolic syndrome on oral hesperidin therapy.  Cellular mechanisms of action of hesperetin were evaluated in bovine aortic endothelial cells (BAEC) in primary culture. A randomized, placebo-controlled, double-blind, crossover trial examined whether oral hesperidin administration (500 mg once daily for 3 wk) improves endothelial function in individuals with metabolic syndrome (n = 24).



We measured the difference in brachial artery flow-mediated dilation between placebo and hesperidin treatment periods.



Treatment of BAEC with hesperetin acutely stimulated phosphorylation of Src, Akt, AMP kinase, and endothelial NO synthase to produce NO; this required generation of H(2)O(2). Increased adhesion of monocytes to BAEC and expression of vascular cell adhesion molecule-1 in response to TNF-α treatment was reduced by pretreatment with hesperetin. In the clinical study, when compared with placebo, hesperidin treatment increased flow-mediated dilation (10.26 ± 1.19 vs. 7.78 ± 0.76%; P = 0.02) and reduced concentrations of circulating inflammatory biomarkers (high-sensitivity C-reactive protein, serum amyloid A protein, soluble E-selectin).



Novel mechanisms for hesperetin action in endothelial cells inform effects of oral hesperidin treatment to improve endothelial dysfunction and reduce circulating markers of inflammation in our exploratory clinical trial. Hesperetin has vasculoprotective actions that may explain beneficial cardiovascular effects of citrus consumption.
Recombinant human erythropoietin in the anemia associated with multiple myeloma or non-Hodgkin's lymphoma: dose finding and identification of predictors of response.

Previous phase I-II clinical trials have shown that recombinant human erythropoietin (rHuEpo) can ameliorate anemia in a portion of patients with multiple myeloma (MM) and non-Hodgkin's lymphoma (NHL). Therefore, we performed a randomized controlled multicenter study to define the optimal initial dosage and to identify predictors of response to rHuEpo. A total of 146 patients who had hemoglobin (Hb) levels < or = 11 g/dL and who had no need for transfusion at the time of enrollment entered this trial. Patients were randomized to receive 1,000 U (n = 31), 2,000 U (n = 29), 5,000 U (n = 31), or 10,000 U (n = 26) of rHuEpo daily subcutaneously for 8 weeks or to receive no therapy (n = 29). Of the patients, 84 suffered from MM and 62 from low- to intermediate-grade NHL, including chronic lymphocytic leukemia; 116 of 146 (79%) received chemotherapy during the study. The mean baseline Hb level was 9.4 +/- 1.0 g/dL. The median serum Epo level was 32 mU/mL, and endogenous Epo production was found to be defective in 77% of the patients, as judged by a value for the ratio of observed-to-predicted serum Epo levels (O/P ratio) of < or = 0.9. An intention-to-treat analysis was performed to evaluate treatment efficacy. The median average increase in Hb levels per week was 0.04 g/dL in the control group and -0.04 (P = .57), 0.22 (P = .05), 0.43 (P = .01), and 0.58 (P = .0001) g/dL in the 1,000 U, 2,000 U, 5,000 U, and 10,000 U groups, respectively (P values versus control). The probability of response (delta Hb > or = 2 g/dL) increased steadily and, after 8 weeks, reached 31% (2,000 U), 61% (5,000 U), and 62% (10,000 U), respectively. Regression analysis using Cox's proportional hazard model and classification and regression tree analysis showed that serum Epo levels and the O/P ratio were the most important factors predicting response in patients receiving 5,000 or 10,000 U. Approximately three quarters of patients presenting with Epo levels inappropriately low for the degree of anemia responded to rHuEpo, whereas only one quarter of those with adequate Epo levels did so. Classification and regression tree analysis also showed that doses of 2,000 U daily were effective in patients with an average platelet count greater than 150 x 10(9)/L. About 50% of these patients are expected to respond to rHuEpo. Thus, rHuEpo was safe and effective in ameliorating the anemia of MM and NHL patients who showed defective endogenous Epo production. From a practical point of view, we conclude that the decision to use rHuEpo in an individual anemic patient with MM or NHL should be based on serum Epo levels, whereas the choice of the initial dosage should be based on residual marrow function.
Predicted Variables in Programming

We present Predicted Variables (PVars), an approach to making machine learning (ML) a first class citizen in programming languages. There is a growing divide in approaches to building systems: using human experts (e.g. programming) on the one hand, and using behavior learned from data (e.g. ML) on the other hand. PVars aim to make ML in programming as easy as ‘if’ statements and with that hybridize ML with programming. We leverage the existing concept of variables and create a new type, a predicted variable. PVars are akin to native variables with one important distinction: PVars determine their value using ML when evaluated. We describe PVars and their interface, how they can be used in programming, and demonstrate the feasibility of our approach on three algorithmic problems: binary search, Quicksort, and caches. We show experimentally that PVars are able to improve over the commonly used heuristics and lead to a better performance than the original algorithms. As opposed to previous work applying ML to algorithmic problems, PVars have the advantage that they can be used within the existing frameworks and do not require the existing domain knowledge to be replaced. PVars allow for a seamless integration of ML into existing systems and algorithms. Our PVars implementation currently relies on standard Reinforcement Learning (RL) methods. To learn faster, PVars use the heuristic function, which they are replacing, as an initial function. We show that PVars quickly pick up the behavior of the initial function and then improve performance beyond that without ever performing substantially worse – allowing for a safe deployment in critical applications.
Hp-Apriori: Horizontal parallel-apriori algorithm for frequent itemset mining from big data

Due to large scale and complexity of big data, mining the big data using a single personal computer is a difficult problem. With increasing in the size of databases, parallel computing systems can cause considerable advantages in the data mining applications by means of the exploitation of data mining algorithms. Parallelization of association rule mining algorithms is an important task in data mining to mine frequent patterns from transaction databases. These algorithms either distribute database horizontally or increase number of CPU to reduce execution time of frequent pattern mining. In this paper, a novel frequent itemset mining algorithm, namely Horizontal parallel-Apriori (HP-Apriori), is proposed that divides database both horizontally and vertically with partitioning mining process into four sub-processes so that all four tasks are performed in parallel way. Also the HP-Apriori tries to speed up the mining process by an index file that is generated in the first step of algorithm. The proposed algorithm has been compared with Count Distribution (CD) in terms of execution time and speedup criteria on the four real datasets. Experimental results demonstrated that the HP-Apriori outperforms over CD in terms of minimizing execution time and maximizing speedup in high scalability.
Jacobian analysis for lower mobility parallel robots based on actuating wrenches

The lower mobility parallel robots have been applied in lots of industrial fields, and the Jacobian plays an important role in the robotic performance analysis such as velocity analysis, precision analysis, and stiffness analysis. As for lower mobility parallel robots with the special limb structures, a novel approach based on actuating wrenches is proposed for the Jacobian analysis, which is much concise compared with the existing methods and significant for the proposed physical concept of the actuating wrench. The characteristics of the special limb structures are explored, and these structures are frequently adopted to constitute the lower mobility parallel robots that are extensively utilized in industry. The Jacobian matrix is derived just through the actuating wrenches. Not only the velocity Jacobian but also the force Jacobian is analyzed, and some incorrect deduction between the two Jacobian matrices appeared in the published works is clarified. Examples show that if the origin of the global coordinate frame is set at the moving platform, the Jacobian analysis can be much simplified.
Reclaimed water as a reservoir of antibiotic resistance genes: distribution system and irrigation implications

Treated wastewater is increasingly being reused to achieve sustainable water management in arid regions. The objective of this study was to quantify the distribution of antibiotic resistance genes (ARGs) in recycled water, particularly after it has passed through the distribution system, and to consider point-of-use implications for soil irrigation. Three separate reclaimed wastewater distribution systems in the western U.S. were examined. Quantitative polymerase chain reaction (qPCR) was used to quantify ARGs corresponding to resistance to sulfonamides (sul1, sul2), macrolides (ermF), tetracycline [tet(A), tet(O)], glycopeptides (vanA), and methicillin (mecA), in addition to genes present in waterborne pathogens Legionella pneumophila (Lmip), Escherichia coli (gadAB), and Pseudomonas aeruginosa (ecfx, gyrB). In a parallel lab study, the effect of irrigating an agricultural soil with secondary, chlorinated, or dechlorinated wastewater effluent was examined in batch microcosms. A broader range of ARGs were detected after the reclaimed water passed through the distribution systems, highlighting the importance of considering bacterial re-growth and the overall water quality at the point of use (POU). Screening for pathogens with qPCR indicated presence of Lmip and gadAB genes, but not ecfx or gyrB. In the lab study, chlorination was observed to reduce 16S rRNA and sul2 gene copies in the wastewater effluent, while dechlorination had no apparent effect. ARGs levels did not change with time in soil slurries incubated after a single irrigation event with any of the effluents. However, when irrigated repeatedly with secondary wastewater effluent (not chlorinated or dechlorinated), elevated levels of sul1 and sul2 were observed. This study suggests that reclaimed water may be an important reservoir of ARGs, especially at the POU, and that attention should be directed toward the fate of ARGs in irrigation water and the implications for human health.
Replacing Username / Password with Software-Only Two-Factor Authentication

It is basically a solved problem for a server to authenticate itself to a client using standard methods of Public Key cryptography. The Public Key Infrastructure (PKI) supports the SSL protocol which in turn enables this functionality. The single-point-of-failure in PKI, and hence the focus of attacks, is the Certi cation Authority. However this entity is commonly o -line, well defended, and not easily got at. For a client to authenticate itself to the server is much more problematical. The simplest and most common mechanism is Username/Password. Although not at all satisfactory, the only onus on the client is to generate and remember a password and the reality is that we cannot expect a client to be su ciently sophisticated or well organised to protect larger secrets. However Username/Password as a mechanism is breaking down. So-called zero-day attacks on servers commonly recover les containing information related to passwords, and unless the passwords are of su ciently high entropy they will be found. The commonly applied patch is to insist that clients adopt long, complex, hard-to-remember passwords. This is essentially a second line of defence imposed on the client to protect them in the (increasingly likely) event that the authentication server will be successfully hacked. Note that in an ideal world a client should be able to use a low entropy password, as a server can limit the number of attempts the client can make to authenticate itself. The often proposed alternative is the adoption of multifactor authentication. In the simplest case the client must demonstrate possession of both a token and a password. The banks have been to the forefront of adopting such methods, but the token is invariably a physical device of some kind. Cryptography's embarrassing secret is that to date no completely satisfactory means has been discovered to implement two-factor authentication entirely in software. In this paper we propose such a scheme.
Erasing Lane Changes From Roads: A Design of Future Road Intersections

Imagine in the future that autonomous vehicles coordinated and guided by signal-free autonomous intersections are able to pass through the intersections immediately after the vehicles in the conflicting direction leave. Meanwhile, with the coordination of the autonomous intersections, autonomous vehicles on any approaching lane are able to turn onto any downstream lane, expecting that driving in such a road system, autonomous vehicles can reach their destinations without any on-road lane changes, and high traffic efficiency will be achieved as well as great traffic safety. To draw the picture in detail, this paper designs a signal-free autonomous intersection with all-direction turn lanes (ADTL) under the environment of autonomous vehicles, and proposes a conflict-avoidance-based approach to coordinate all approaching vehicles in different directions. Communicating with the approaching autonomous vehicles and utilizing the approach, the autonomous ADTL intersection is able to coordinate the approaching vehicles in all directions and guide them to safely and efficiently pass through the intersection. Two simulation scenarios are conducted in a road network with an isolated intersection composed of four three-lane arms. One scenario validates the collision-free design of the system, and the other shows that the designed ADTL intersection outperforms the conventional signal controlled intersection in terms of traffic efficiency, and is potentially better than the autonomous intersection with specific-direction turn lanes. The autonomous ADTL intersection can be an important basis for designing a future autonomous urban road traffic system.
Dial One for Scam: A Large-Scale Analysis of Technical Support Scams

In technical support scams, cybercriminals attempt to convince users that their machines are infected with malware and are in need of their technical support. In this process, the victims are asked to provide scammers with remote access to their machines, who will then “diagnose the problem”, before offering their support services which typically cost hundreds of dollars. Despite their conceptual simplicity, technical support scams are responsible for yearly losses of tens of millions of dollars from everyday users of the web. In this paper, we report on the first systematic study of technical support scams and the call centers hidden behind them. We identify malvertising as a major culprit for exposing users to technical support scams and use it to build an automated system capable of discovering, on a weekly basis, hundreds of phone numbers and domains operated by scammers. By allowing our system to run for more than 8 months we collect a large corpus of technical support scams and use it to provide insights on their prevalence, the abused infrastructure, the illicit profits, and the current evasion attempts of scammers. Finally, by setting up a controlled, IRB-approved, experiment where we interact with 60 different scammers, we experience first-hand their social engineering tactics, while collecting detailed statistics of the entire process. We explain how our findings can be used by law-enforcing agencies and propose technical and educational countermeasures for helping users avoid being victimized by technical support scams.
Subsymptomatic Aerobic Exercise for Patients With Postconcussion Syndrome: A Critically Appraised Topic.

Patients who experience prolonged concussion symptoms can be diagnosed with postconcussion syndrome (PCS) when those symptoms persist longer than 4 weeks. Aerobic exercise protocols have been shown to be effective in improving physical and mental aspects of health. Emerging research suggests that aerobic exercise may be useful as a treatment for PCS, where exercise allows patients to feel less isolated and more active during the recovery process.



Is aerobic exercise more beneficial in reducing symptoms than current standard care in patients with prolonged symptoms or PCS lasting longer than 4 weeks?  After a thorough literature search, 4 studies relevant to the clinical question were selected. Of the 4 studies, 1 study was a randomized control trial and 3 studies were case series. All 4 studies investigated aerobic exercise protocol as treatment for PCS. Three studies demonstrated a greater rate of symptom improvement from baseline assessment to follow-up after a controlled subsymptomatic aerobic exercise program. One study showed a decrease in symptoms in the aerobic exercise group compared with the full-body stretching group.  There is moderate evidence to support subsymptomatic aerobic exercise as a treatment of PCS; therefore, it should be considered as a clinical option for reducing PCS and prolonged concussion symptoms. A previously validated protocol, such as the Buffalo Concussion Treadmill test, Balke protocol, or rating of perceived exertion, as mentioned in this critically appraised topic, should be used to measure baseline values and treatment progression. Strength of Recommendation: Level C evidence exists that the aerobic exercise protocol is more effective than the current standard of care in treating PCS.
The pyramid match kernel: discriminative classification with sets of image features

Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondences epsivnerally a computationally expensive task that becomes impractical for large set sizes. We present a new fast kernel function which maps unordered feature sets to multi-resolution histograms and computes a weighted histogram intersection in this space. This "pyramid match" computation is linear in the number of features, and it implicitly finds correspondences based on the finest resolution histogram cell where a matched pair first appears. Since the kernel does not penalize the presence of extra features, it is robust to clutter. We show the kernel function is positive-definite, making it valid for use in learning algorithms whose optimal solutions are guaranteed only for Mercer kernels. We demonstrate our algorithm on object recognition tasks and show it to be accurate and dramatically faster than current approaches
Design of retuning fractional PID controllers for a closed-loop magnetic levitation control system

In this paper, we study the problem of fractional-order PID controller design for an unstable plant-a laboratory model of a magnetic levitation system. To this end, we apply model based control design. A model of the magnetic lévitation system is obtained by means of a closed-loop experiment. Several stable fractional-order controllers are identified and optimized by considering isolated stability regions. Finally, a nonintrusive controller retuning method is used to incorporate fractional-order dynamics into the existing control loop, thereby enhancing its performance. Experimental results confirm the effectiveness of the proposed approach. Control design methods offered in this paper are general enough to be applicable to a variety of control problems.