Miracle-dz/UniFAR-FTUs huggingface dataset:
Correction of Temporal Hollowing With the Superior Gluteal Artery Perforator Free Flap

Abstract Temporal hollowing is most frequently an acquired deformity and can be caused by volume defects of bone, soft tissue, or both. Recently, surgical reconstruction with autogenous fat or allografts has been introduced, but these materials can be resorbed over time and may also lead to infection. Herein, the authors present 2 cases demonstrating the treatment of temporal hollowing with a superior gluteal artery perforator (SGAP) free flap. Both patients had a history of traffic accidents and subsequent craniectomy because of subdural hemorrhage, followed by cranioplasty. An SGAP free flap was selected to reconstruct the soft tissue temporal defect in both patients. Pre-operatively, computed tomography (CT) angiography was used to locate the superior temporal artery (STA). A preauricular incision provided surgical access to the STA, and a subcutaneous pocket was created. The STA and SGAP artery and vein anastomoses were performed. Before flap insetting, it was de-epithelized, and its volume and shape trimmed to fit into the temporal defect. The patients’ post-operative courses were without complications, and facial symmetry was achieved. This is the first case report describing the microvascular reconstruction of temporal hollowing with an SGAP free flap. The SGAP free flap is permanent and highly vascularized with no risk of infection. These case reports illustrate a unique reconstruction technique that resulted in a satisfactory outcome for the patients.
Tomato Brown Rugose Fruit Virus Contributes to Enhanced Pepino Mosaic Virus Titers in Tomato Plants

The tobamovirus tomato brown rugose fruit virus (ToBRFV), a major threat to tomato production worldwide, has recently been documented in mixed infections with the potexvirus pepino mosaic virus (PepMV) CH2 strain in traded tomatoes in Israel. A study of greenhouse tomato plants in Israel revealed severe new viral disease symptoms including open unripe fruits and yellow patched leaves. PepMV was only detected in mixed infections with ToBRFV in all 104 tested sites, using serological and molecular analyses. Six PepMV isolates were identified, all had predicted amino acids characteristic of CH2 mild strains excluding an isoleucine at amino acid position 995 of the replicase. High-throughput sequencing of viral RNA extracted from four selected symptomatic plants showed solely the ToBRFV and PepMV, with total aligned read ratios of 40.61% and 11.73%, respectively, indicating prevalence of the viruses. Analyses of interactions between the co-infecting viruses by sequential and mixed viral inoculations of tomato plants, at various temperatures, showed a prominent increase in PepMV titers in ToBRFV pre-inoculated plants and in mixed-infected plants at 18–25 °C, compared to PepMV-single inoculations, as analyzed by Western blot and quantitative RT-PCR tests. These results suggest that Israeli mild PepMV isolate infections, preceded by ToBRFV, could induce symptoms characteristic of PepMV aggressive strains.
Effect of Self Efficacy and Integrity to Organizational Performance through Commitment Organization in PT Rekayasa Engineering Jakarta

DOI: 10.21276/sjebm.2018. 5.11. 8 Abstract: This study aims to identify and analyze the effect of self-efficacy and integrity of the performance of the organization through organizational commitment variable. The study was conducted on the organization of PT. Rekayasa Engineering Jakarta. Sampling using saturated samples involving 83 employees in all parts of the organization. Analysis of data using path analysis. Based on the survey results revealed that the variables of self-efficacy and integrity effect on organizational performance through organizational commitment. The direct effect of self-efficacy and integrity of the organization's performance is less than the indirect effect so that it can be said that the organizational commitment variable as an intervening variable.
Social Movement Organizations in Online Protest Movements

In the era of Web 2.0, social media based Internet activism is slowly replacing traditional civic engagements such as sit-ins, strikes, rallies, etc. Proponents of online activism postulate that low participation and coordination costs, and the decentralized structure of these platforms will render the services and functionalities provided by Social Movement Organizations (SMOs) nonessential. Yet, such claims currently lack empirical evidence since many existing studies do not distinguish the participation of SMOs from individuals, and are therefore unable to determine the value of SMOs in online protest movements. This paper aims to fill that knowledge gap. First, we use large-scale crowdsourcing platforms in combination with nested supervised learning models and identify more than 50 thousand SMOs participating in 2 distinct Twitter hashtag movements; next, by characterizing their primary objectives, we further assign each SMO to a specific social movement industry (SMI). We explore the attributes of these SMOs from five different perspectives: commitment, knowledge sharing, community building, structural significance and recruitment. We find that SMOs utilize a more diverse knowledge base, are more consistent and committed in their participation, apply more community-building efforts, possess more favorable positions within online protest networks, and contributed substantially to the recruitment of new participants compared to nonsocial movement organizations and individuals. We further compare and contrast behavior differences of SMOs from different SMIs. In summary, our findings show that the role of SMOs in social movements is far from over, even when focusing on online movements. In fact, social media affordances are allowing SMOs to participate together in a scope that is unattainable by traditional protesting methods. ACM Reference format: . 2018. Social Movement Organizations in Online Protest Movements. In Proceedings of ACM Woodstock conference, Lyon, France, April 2018 (WWW’18),
Hydrology and fire regulate edge influence on microclimate in wetland forest patches

Differences in temperature, relative humidity, and vapor pressure deficit (VPD) were observed within small patches of pondcypress (Taxodium distichum var. imbricarium) compared with adjacent, largely treeless, vegetation communities. These patches, locally called cypress domes, displayed increasing differences in microclimate between their exterior or edges and interiors with increasing distance toward their centers. We sought to assess whether seasonal inundation of these small swamps results in a hydrologic switch in which the presence of standing water overwhelms the effects of edge distance on microclimate variation. Hydrology does appear to exert substantial control over the edge effect on microclimate, but the effects of distance from the edge remained discernable during periods of inundation. We also studied the effects of a wildfire that occurred 2 y before data collection. We expected to find warmer and drier conditions in domes affected by recent fire. Contrary to our expectations, previously burned domes were either similar to unburned domes or, in some cases, cooler and more humid than unburned domes, possibly because of vigorous regrowth after fire in these highly productive, fire-adapted subtropical ecosystems.
Comparative Analysis of Image Processing Algorithms for Airport Security

In the current age of increased air travel, safe airport security is imperative. And while correctly detecting potential threats is a top priority, it is also important that these security checks are performed as efficiently as possible to maintain the flow of travel. Current security methods utilize machine learning algorithms to analyze and detect threats on millimeter wave scans of individuals. This paper implemented and compared various classification algorithms on a dataset of millimeter waves scans to determine the most effective algorithm at detecting threats. This paper also examined different data preprocessing and model optimization techniques and their effect on the performance of the models. It was concluded that the convolutional neural network and long short-term memory network, trained on a specific zone of the body, were the most effective models for detecting potential threats.
Who Is Left Out? The Process of Validating Voter Registration Applications

Whose voter registration requires further verification and why? And why are some prospective registrants left out from voter records? These questions can uncover challenges in the voter registration process, and potential implementation issues with federal and state law. In this article, I analyze “on hold” voter registration applications processed between November 2007 and September 2008 in Florida’s Hillsborough and Miami-Dade Counties. I evaluate why individuals were left out of the voter rolls, by matching their records to snapshots of the counties’ voter records from December 2008. I find that “on hold” applicants face persistent challenges in successfully registering to vote, particularly depending on when they attempt to register and what type of information they omit from a voter registration application.
Effect of FYM and Fe-Zn-S supplementation on yield and quality of multicut forage sorghum (cv. SSG-59-3).

Eighteen treatments comprising of combination of three levels of FYM (0, (F 0 ), 10 (F 1 ) and 20 (F 2 ) t ha) and six nutrient management treatments [control (M 0 ), Fe (M 1 ), Zn (M 2 ), S (M 3 ), Fe + Zn (M 4 ) and Fe + Zn + S (M 5 )] were tested in factorial randomized block design with three replications in field experiments conducted during Kharif and summer seasons of 2003 and 2004. Fe, Zn and S were applied @ 10, 5 and 40 kg ha as FeSO 4 , ZnSO 4 and gypsum, respectively. Initial available S, Fe and Zn contents in the soil were low. Yield of green forage and dry forage were increased by the treatments F 2 and F 1 (8.5 and 5.3 %, respectively) over treatment F 0 . The treatments M 5 and M 4 significantly increased the green fodder yield by 13.0 and 8.5 per cent, respectively, over that of M 0 (731.5 q ha). The study of quality parameters viz., crude protein content, neutral detergent fiber and sugar content revealed that application of FYM at F 1 and F 2 as well as Fe-Zn-S treatments favourably influenced the quality parameters in comparison to their respective control.
On the Application of Cultured Neuronal Cell Lines in Neurotoxicological Studies: Cytotoxicity of Acrylamide

Summary Acrylamide, a well known neurotoxic compound, was used in a first evaluation of cultured mouse neuroblastoma cells as an alternative to animal models for neurotoxicological studies. Hence, the effects of acrylamide on the growth, size, morphology and leucine incorporation of three neuroblastoma (41A3, N18 and N1E115), one neuroblastoma x glioma hybrid (NG108CC15), two glioma (138MG and C6) and two fibroblast (RLF and RMC) cell lines were studied. It was found that the concentration of acrylamide needed to inhibit the growth by 50% in 24 hr was similar in all cell lines, i.e. around 2 x 10-4g/ml culture medium. In the two cell lines, N1E115 and NG108CC15, acrylamide at this concentration caused neurite retraction and at higher concentrations (5 x 10-4g/ml) a decrease in cell viability. In a concentration range of 5 x 10-5 - 5 x 10-4g/ml acrylamide did not affect cell size, or at 2 x 10-4g/ml incorporation of leucine into trichloroacetic acid precipitable material. It is suggested that acrylamide interferes with a biochemical process common to all the tested cells, but of greater importance in differentiated nerve cells than in others. Whether this process is consistent with the in vivo target for the neurotoxic action of acrylamide remains to be unravelled.
Comparison of Endpoint Admission Control Algorithms by probing at Exponential Interval and at Constant Interval

Summary An Endpoint admission control adopts probing at a constant rate equivalent to peak rate of the flow to be admitted. This inserts a large burst of packets. The real-time traffic flows by nature do not require such large chunk of bandwidth because of their VBR characteristics. This has prompted to use exponential interval probing to determine the spare bandwidth. With such probing, admission decision based on both packet loss and variants of inter-packet delay estimation are evaluated. It is found that probing at exponential interval and admission decision taken based on the proposed admission algorithm which works on estimation of average inter-packet delay result in a better performance in terms of improved bottleneck link utilization and also a lower inter-packet delay variation being experienced by the admitted data flows.
Activation Calculations with FLUKA for the BERLinPro Vacuum System

In 2012 the Helmholtz-Zentrum Berlin finished the c on eptual design report of B ERLinPro – a prototype of the Energy Recovery Linac (ERL) technology. The max i um electron energy is 50 MeV, the maximum current is 100 mA (cw), low energy parts of the mac hine (injector, beam dump line) are operated at abo ut 10 MeV. Due to the high beam power of 5 MW in the ring the machine will be built subterraneously at the BESSYII site. Dedicated assessments concerning radi ation protection issues have been done so far in or der to determine a detailed radiation safety concept an d to obtain the construction permit by using the Mo nteCarlo-Code Fluka. One important issue is the dose caused by activatio n of the vacuum system, since several accesses into the accelerator hall will be necessary because of a cer t in amount of maintenance. Therefore different sce narios after switching off the machine are simulated with FLUKA. For these simulations we suppose a constant electron loss of 5 μA/m during operation of the machine and determined the doses at different times after a switch-off for an aluminium alloy and steel. As a r esult the vacuum system will be constructed out of aluminium except a few parts of steel (due to mecha nical reasons).
A Comprehensive Quality Evaluation of Security and Privacy Advice on the Web

End users learn defensive security behaviors from a variety of channels, including a plethora of security advice given in on-line articles. A great deal of e ﬀ ort is devoted to getting users to follow this advice. Surprisingly then, little is known about the quality of this advice: Is it comprehensible? Is it actionable? Is it e ﬀ ective? To answer these questions, we ﬁrst conduct a large-scale, user-driven measurement study to identify 374 unique recommended behaviors contained within 1,264 documents of online security and privacy advice. Second, we develop and validate measurement approaches for evaluating the quality – comprehensibility, perceived actionability, and perceived e ﬃ cacy – of security advice. Third, we deploy these measurement approaches to evaluate the 374 unique pieces of security advice in a user-study with 1,586 users and 41 professional security experts. Our results suggest a crisis of advice prioritization. The majority of advice is perceived by the most users to be at least somewhat actionable, and somewhat comprehensible. Yet, both users and experts struggle to prioritize this advice. For example, experts perceive 89% of the hundreds of studied behaviors as being e ﬀ ective, and identify 118 of them as being among the “top 5” things users should do, leaving end-users on their own to prioritize and take action to protect themselves.
The Effects of Some Non-steroidal Antiinflammatory Drugs on Human Granulopoiesis In Vitro

By measuring colony forming units in culture (CFU-C), the effects of the non-steroidal antiinflammatory drugs indoprofen (24mg/1; 39μM), indomethacin (24mg/1; 67μM), and phenylbutazone (12mg/l; 39μM) on human granulopoiesis in vitro were compared with those of chloramphenicol (57mg/l; 176μM) in 18 bone marrow samples. Inhibitions of 10–92% (median 54%) for indoprofen, -13–86% (median 34%) for ibuprofen, 0–86% (median 42%) for indomethacin and -26–75% (median 3%) for phenylbutazone were observed, with chloramphenicol showing inhibitions of 11–100% (median 70%). A further patient, who had developed agranulocytosis during indoprofen treatment, subsequently showed no greater sensitivity to that drug in vitro than the other patients studied. This in vitro technique may be useful in Phase I studies on new drugs.
Empirical Research on the Influencing Factors of Purchase Intention in Catering Online Group-buying

It is becoming more and more popular that consumers group buy catering online, The study chose the empirical research variables and used questionnaires to analyze the factors which affect purchase intention of catering online group-buying consumers through presenting the theories of consumer behavior and intention about catering online group-buying. The result shows that perceived usefulness and of consumers both have a positive impact on consumers' cognitive value. Besides, cognitive value, the brand word-of-mouth and the characteristics of meal coupons have a positive influence on the consumer intention about catering online group-buying, while perceived risk has a negative effect on it.
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Predicting Intraday Return Patterns based on Overnight Returns for the US Stock Market

This paper investigates predicting intraday return patterns conditional on observed overnight returns. Based on Trade and Quote data, we find evidence for dependence between overnight returns and subsequent intraday first and last half-hour return patterns for the S&P 500 Exchange-Traded Fund for the time period from 2003 to 2013 with both statistical and economic significance. Our methodology allows studying the return patterns documented in the existing theoretical and empirical literature in more detail. Moreover, we find that both the first and the last half-hours offer trading opportunities for day traders. Specifically, 20-minute after the market opens and the last 30-minute before the market closes seem to be the best holding periods for investors in terms of annualized returns, Sharpe ratios, and Certainty
A CAPM-Based Model with Feedback Traders, Time-Varying Volatility and Asymmetric News Impact Curve

This work derives an Intertemporal CAPM-based model that incorporates a feedback traderse¤ect in the form of rst-lag serial correlations. In the proposed model, we use a non-standard market equilibrium condition that links traders demand to current market value (wealth distribution over time) and not just to the market portfolio (wealth distribution over assets). The market risk is modeled with a Threshold-GARCH in-mean model in order to account for Time-varying conditional variances of the assetsreturns and asymmetric news impact curve. The model is estimated on weekly returns of the S&P index over the years 1980-2008. The empirical analysis reject the Intertemporal CAPM and reveals that relation between expected returns and risk is highly nonlinear. We also nd evidence that both returns and conditional variances are serially correlated.
Combining ability of maize inbred lines (Zea mays L.) for yields in mid altitude sub-humid Agroecology of Ethiopia

Maize is an important staple food for most Ethiopians, but the national average productivity of maize is below that of the world. Development and cultivation of high yielding maize hybrids can improve maize productivity and production. Having information on combining ability and heterosis of maize inbred lines is important for the development of high yielding maize hybrids. The objectives of this study were to identify good hybrids based on grain yield and yield related traits, to estimate the general combining ability (GCA) and specific combining ability (SCA). Thirteen inbred lines were crossed in 2017 with two line testers using a line by tester mating design. The resulting 26 crosses were evaluated in a randomized incomplete block design (RCBD) with three replications during the main rainy seasons between June and November, 2018 at Bako, Ethiopia. In addition, the 13 parental lines including the two tester lines were evaluated using RCBD with three replications in a separate trial. Analysis of variance (ANOVA) showed that mean squares due to crosses were highly significant (P≤0.01) for most of the traits studied, except ear aspect. Also mean square due to line was significantly different (P < 0.01 or P < 0.05) in all studied traits except days to anthesis (AD) and ear aspect (EA). The overall mean grain yields (GY) of the hybrids were 6.32 t/ha ranging from 5.21 to 8.19 t/ha. L7 had the lowest negative GCA for grain yield whereas L6 had the highest positive GCA. Among the crosses with high positive SCA, estimates showed high mean grain yield, which implied good correspondence between SCA effects and mean GY. The result obtained in this study could be useful to design for developing high yielding hybrids and synthetics adapted to the mid altitude sub humid agro ecologies of Ethiopia. Key words: Grain yield, maize inbred lines, line by tester, general combining ability, specific combining ability.
Robust k-means++

A good seeding or initialization of cluster centers for the k -means method is important from both theoretical and practical stand-points. The k -means objective is inherently non-robust and sensitive to outliers. A popular seeding such as the k -means++ [3] that is more likely to pick outliers in the worst case may compound this drawback, thereby aﬀecting the quality of clustering on noisy data. For any 0 < δ ≤ 1, we show that using a mixture of D 2 [3] and uniform sampling, we can pick O ( k/δ ) candidate centers with the following guarantee: they contain some k centers that give O (1)-approximation to the optimal robust k -means solution while discarding at most δn more points than the outliers discarded by the optimal so-lution. That is, if the optimal solution discards its farthest βn points as outliers, our solution discards its ( β + δ ) n points as outliers. The constant factor in our O (1)- approximation does not depend on δ . This is an improvement over previous results for k -means with outliers based on LP relaxation and rounding [7] and local search [17]. The O ( k/δ ) sized subset can be found in time O ( ndk ). Our robust k -means++ is also easily amenable to scalable, faster, parallel implementations of k -means++ [5]. Our empirical results show a comparison of the above robust variant of k -means++ with the usual k -means++, uniform random seeding, threshold k -means++ [6] and local search on real world and synthetic data.