Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Tandem Mass Tag Labeling Method for Lipid Molecules Containing Carboxy and Phosphate Groups, and Their Stability in Human Serum

In clinical lipidomics, it is a challenge to measure a large number of samples and to reproduce the quantitative results. We expanded the range of application of the tandem mass tag (TMT) method, which is widely used in proteomics, to lipidomic fields. There are various types of lipid molecule, for example, eicosanoids have a carboxyl group and phosphatidic acid has a phosphate group. We modified these functional groups simultaneously with TMT. This approach allows for a single analysis by mixing six samples and using one of the six samples as a bridging sample; the quantitative data can be easily normalized even if the number of measurements increases. To accommodate a large number of samples, we utilize a pooled serum sample of 300 individuals as a bridging sample. The stability of these lipid molecules in serum was examined as an analytical validation for the simultaneous TMT labeling. It was found that the stability of these lipid molecules in serum differs greatly depending on the lipid species. These findings reaffirmed the importance of proper sample preparation and storage to obtain reliable data. The TMT labeling method is expected to be a useful method for lipidomics with high-throughput and reliable reproducibility.
Activity of murine surrogate antibodies for durvalumab and tremelimumab lacking effector function and the ability to deplete regulatory T cells in mouse models of cancer

ABSTRACT Preclinical studies of PD-L1 and CTLA-4 blockade have relied heavily on mouse syngeneic tumor models with intact immune systems, which facilitate dissection of immunosuppressive mechanisms in the tumor microenvironment. Commercially developed monoclonal antibodies (mAbs) targeting human PD-L1, PD-1, and CTLA-4 may not demonstrate cross-reactive binding to their mouse orthologs, and surrogate anti-mouse antibodies are often used in their place to inhibit these immune checkpoints. In each case, multiple choices exist for surrogate antibodies, which differ with respect to species of origin, affinity, and effector function. To develop relevant murine surrogate antibodies for the anti-human PD-L1 mAb durvalumab and the anti-human CTLA-4 mAb tremelimumab, rat/mouse chimeric or fully murine mAbs engineered for reduced effector function were developed and compared with durvalumab and tremelimumab. Characterization included determination of target affinity, in vivo effector function, pharmacokinetic profile, and anti-tumor efficacy in mouse syngeneic tumor models. Results showed that anti–PD-L1 and anti–CTLA-4 murine surrogates with pharmacologic properties similar to those of durvalumab and tremelimumab demonstrated anti-tumor activity in a subset of commonly used mouse syngeneic tumor models. This activity was not entirely dependent on antibody-dependent cellular cytotoxicity, antibody-dependent cellular phagocytosis effector function, or regulatory T-cell depletion, as antibodies engineered to lack these features showed activity in models historically sensitive to checkpoint inhibition, albeit at a significantly lower level than antibodies with intact effector function.
LUMAWIG: Un-bottling the bottleneck distance for zero dimensional persistence diagrams at scale

We present L UMÁWIG , a novel efﬁcient algorithm to compute dimension zero bottleneck distance between two persistence diagrams of a speciﬁc kind which outperforms all other publicly available algorithm in runtime and accuracy. We bypass the overwhelming matching problem in previous implementations of the bottleneck distance, and prove that the zero dimensional bottleneck distance can be recovered from a very small number of matching cases. L UMÁWIG also generally enjoys linear complexity as shown by empirical tests. This allows us to scale TDA to data sets of sizes encountered in machine learning and utilize persistence diagrams in a manner that goes beyond the simple use of the most persistent components 2 .
Survivability-Enhanced Virtual Network Embedding Strategy in Virtualized Wireless Sensor Networks

With the widespread application of wireless sensor networks (WSNs), WSN virtualization technology has received extensive attention. A key challenge in WSN virtualization is the survivable virtual network embedding (SVNE) problem which efficiently maps a virtual network on a WSN accounting for possible substrate failures. Aiming at the lack of survivability research towards physical sensor node failure in the virtualized sensor network, the SVNE problem is mathematically modeled as a mixed integer programming problem considering resource constraints. A heuristic algorithm—node reliability-aware backup survivable embedding algorithm (NCS)—is further put forward to solve this problem. Firstly, a node reliability-aware embedding method is presented for initial embedding. The resource reliability of underlying physical sensor nodes is evaluated and the nodes with higher reliability are selected as mapping nodes. Secondly, a fault recovery mechanism based on resource reservation is proposed. The critical virtual sensor nodes are recognized and their embedded physical sensor nodes are further backed up. When the virtual sensor network (VSN) fails caused by the failure physical node, the operation of the VSN is restored by backup switching. Finally, the experimental results show that the strategy put forward in this paper can effectively guarantee the survivability of the VSN, reduce the failure penalty caused by the physical sensor nodes failure, and improve the long-term operating income of infrastructure provider.
Detecting trends in freshwater trace element concentrations: methodological issues and data treatment

Despite the fact that the increased use of elements linked to the Anthropocene is frequently assumed to lead to an increase in the concentrations of the elements in surface waters, temporal trends of trace element (TE) concentrations have rarely been checked. A temporally extended, traceable dataset of TE concentrations in the waters of Lake Geneva, Switzerland (1996–2015) has been used here to explore methodological and data treatment issues that arise when attempting to rigorously determine temporal trends in freshwater TE concentrations. The trace elements studied (Cd, Co, Gd, Mo, Pb, Sb, Sr) have been chosen to cover a wide range of chemical and utilisation conditions. We show that detecting temporal trends from monitoring program data is feasible, even when trends are weak, provided that rigorous data treatment methods are applied. Aspects related to the effect of data quality are discussed in detail. However, ascertaining the statistical significance of any trends calculated remains a difficult issue. With the exception of Co and Sr, that show no significant changes, and Pb, that shows a general decrease, concentrations in lake waters of the trace elements considered have increased significantly, particularly between 2006 and 2015.
Data-Driven Optimization Control for Dynamic Reconfiguration of Distribution Network

To improve the reliability and reduce power loss of distribution network, the dynamic reconfiguration is widely used. It is employed to find an optimal topology for each time interval while satisfying all the physical constraints. Dynamic reconfiguration is a non-deterministic polynomial problem, which is difficult to find the optimal control strategy in a short time. The conventional methods solved complex model of dynamic reconfiguration in different ways, but only local optimal solutions can be found. In this paper, a data-driven optimization control for dynamic reconfiguration of distribution network is proposed. Through two stages that include rough matching and fine matching, the historical cases which are similar to current case are chosen as candidate cases. The optimal control strategy suitable for the current case is selected according to dynamic time warping (DTW) distances which evaluate the similarity between the candidate cases and the current case. The advantage of the proposed approach is that it does not need to solve complex model of dynamic reconfiguration, and only uses historical data to obtain the optimal control strategy for the current case. The cases study shows that the optimization results and the computation time of the proposed approach are superior to conventional methods.
Normatively Framed Relative Performance Feedback – Field Experiment and Replication

Feedback can help individuals put their performance into perspective, especially when transitioning into a new environment such as university or a different job. In a randomized field experiment we give first-year university students normatively framed relative performance feedback about their accumulated course credits. We find an increase in subsequent performance, but only when the feedback is positive. Using a regression discontinuity design, we show that the improved performance is not driven by unobserved characteristics of those receiving positive feedback, but that it is indeed due to the positive rather than negative nature of the feedback. We administer a replication experiment with the next wave of first-year students one year later and reproduce the results. Survey data provides suggestive evidence that positive feedback has an effect on behavior when students underestimate their relative performance, and that consistent with a mechanism of selective information processing, individuals focus on positive feedback to adjust their beliefs.
Chronological schemes of the Late Hallstatt period (HaD) in Central Europe: new opportuni-ties for the synchronization and refinement of dates

Unification of regional chronological schemes is one of the key issues in Early Iron Age archaeology. The main markers of the Late Hallstatt period are Scythian arrowheads and antique imports. Biconical glass beads, produced at the Yahorlyk settlement (in the first third of the VIth century BC), were found in the Eastern European Forest-Steppe and in the area of the Tarnobrzeg Lusatian Culture. This period is synchronised with the HaD1 of Central Europe, phase III/1 of the TLC and the late group of burials of the second phase of the Kelermes period. Its final phase is associated with the so-called “Scythian invasions” in Central Europe, which led to the decline of the Chotyniec agglomeration, West-Podolian and East-Podolian groups. A few TLC complexes of the Grodzisko Dolne, site 22, can be dated somewhat later, to the middle or second half of the VIth century BC (HaD2). Also, at this time, the Pomeranian population appeared in the south-eastern area of the Lusatian tribes and a new culture model (post Lusatian-Pomeranian stage) arose.
FACTORS AFFECTING EMPLOYEE PERFORMANCE IMPROVEMENT ON FINANCE COMPANIES

The purpose of this study is to examine and determine the factors that can affect employee performance improvement in finance companies. The research method used is a quantitative approach. Data were analyzed by Partial Least Square (PLS) statistic tool. This research was conducted at PT. Mandiri Tunas Finance Malang Branch and Pasuruan Satellite. The population in this study were all permanent employees, amounting to 82 people. Furthermore, the entire population became the respondents so that this research used the census method in the sample determination. Based on the result of the research, it can be concluded that the factors that can improve employee performance in finance company are motivation, especially motivation that comes from within the employees themselves (intrinsic motivation) and organizational culture, while leadership can influence the improvement of employee performance if mediated by work motivation. Some suggestions that can be put forward to improve employee performance in finance companies are building employee work motivation, by holding special education program for employees in order to get promotion, continuous training, provides a challenging task, and adequate working facilities; Create a good organizational culture so that it can help employees to make it easier to carry out their work; Recruiting employees who have work experience ranging from 5 years with educational background is a bachelor.
Whale Optimization Algorithm Based Tilt Integral Derivative Control for Frequency Regulation in AC Microgrid with and without SMES

This paper presents the control scheme for frequency regulation against step load perturbations in an AC microgrid using tilt integral derivative (TID) controller, optimally tuned employing whale optimization algorithm (WOA)a recently proposed evolutionary algorithm. The AC microgrid system considered for this study comprises the distributed generation (DG) systemsconsisting primarily the renewable energy sources (RESs)-, energy storage systems (ESSs), and the diesel engine generator (DEG). The performance of the control scheme is assessed in respect of effective regulation of system frequency within nominal limits as judged in terms of peak overshoot/undershoot, settling time and the minimum value of the performance index-integral of time multiplied absolute error (ITAE). For comparative analysis, the performance of the proposed control scheme is judged against the conventional and adaptive network fuzzy inference system (ANFIS)-PID controllers also. Further, the effect of superconducting magnetic energy storage (SMES) on the frequency regulation is also analyzed besides testing the proposed control scheme for stability and robustness against parametric uncertainty & random step load variations. The use of WOA for optimal tuning of TID controller is the novel proposition in this paper which proves to be a very effective strategy in containing the frequency excursions in the AC microgrid under different operating conditions as against the other controllers implemented here. MATLAB/Simulink is used as the platform for system modeling and simulations.
Validasi Metode Analisis Logam Merkuri (Hg) Terlarutn pada Air Permukaan dengan Automatic Mercury Analyzer

Validasi metode analisis adalah suatu penilaian terhadap parameter tertentu, berdasarkan percobaan laboratorium, untuk membuktikan bahwa parameter tersebut memenuhi persyaratan untuk penggunaannya (Harmita, 2004). Penelitian ini bertujuan untuk memvalidasi metode analisis Merkuri (Hg) pada Air permukaan dengan Automatic Mercury Analyzer, sebagai syarat untuk mengajukan parameter terakreditasi International Organization for Standardization/ International Electrotechnical Commission ( ISO/IEC 17025 – 20 17). Validasi metode analisis yang dilakukan mengacu pada International Conference on Harmonization (ICH) dengan menentukan berbagai parameter, yaitu linieritas, sensitivitas (LOD dan LOQ), ketelitian, dan ketepatan. Sampel air permukaan disaring menggunakan kertas saring yang mempunyai pori 0,45 µm, kemudian dianalisis dengan metode Automatic Mercury Analyzer. Metode analisis yang dilakukan memberikan hasil yang linier dengan nilai koefisien korelasi (r) > 0,9992 dan koefisien determinasi (r²) > 0,9984. Nilai batas deteksi (LOD) dalam sampel 0,07 µg/L. Nilai batas kuantitasi (LOQ) dalam sampel 0,24 µg/L. Simpangan baku relatif (RSD) yang diperoleh untuk keterulangan sebesar 3,17 % dan presisi antara sebesar 6,75 %, nilai tersebut kurang dari batas yang diijinkan oleh Horwitz dan AOAC PVM. Penentuan akurasi dengan penetapan persen perolehan kembali sebesar 98,08 %, nilai tersebut berada pada rentang yang diperbolehkan menurut AOAC PVM. Metode yang telah divalidasi kemudian diaplikasikan untuk analisis logam Hg dalam air permukaan, sebagai penjaminan mutu dilakukan uji banding. Hasil uji banding di Badan Pengkajian Teknologi Pertanian (BPTP) Yogyakarta: A= 0,69 µg/L, B= 0,96 µg/L, C= 0,78 µg/L,di Laboratorium Penelitian dan Pengujian Terpadu (LPPT): A= 0,83 µg/L, B= 0,69 µg/L, C= 0,85 µg/L, kemudian diuji dengan independent T-Test, memberikan hasil tidak berbeda bermakna.
A New Tropical Species of Psathyrella (Psathyrellaceae, Agaricales) From the Cúc Phương National Park, Vietnam

Basidiocarps of a hitherto undescribed Psathyrella species were collected during a sampling excursion in North Vietnam. They grew on deciduous deadwood in the Southeastern part of the Cúc Phương National Park (Vietnamese: Vườn quốc gia Cúc Phương), Ninh Bình Province. Herein, we describe Psathyrella euryspora sp. nov. characterized by broadly ellipsoid to broadly ovoid basidiospores (5.5–7.0 × 4–5(–6)) µm without visible germ pore, utriform to ventricose-clavate cheilocystidia, heteromorphic caulocystidia and the absence of pleurocystidia and pileocystidia. Based on an isolated pure culture, the genome was sequenced and a full ribosomal RNA gene cistron including 18S, internal transcribed spacer 1 (ITS), 5.8S, ITS2 and 28S rRNA annotated. Phylogenetic analysis of P. euryspora revealed its close affiliation to the Psathyrella sect. Candolleanae species clade.
Policy Implications of Third-Party Measurement of Interdomain Congestion on the Internet

Internet engineering, science, and public policy communities have significant interest in understanding the extent and scope of, as well as potential consumer harm induced by, persistent interdomain congestion on the Internet. In recent work, we developed and implemented a lightweight active measurement method and system to measure evidence of congestion on thousands of interconnection links between broadband access ISPs and major interconnecting parties, including directly connected content providers. This method provides empirical grounding for discussions of interconnection congestion, without requiring direct access to interconnection links. We first review the previous work to provide context. We then present new techniques for visualizing the data in ways we believe are conducive to policy analysis, e.g, of infrastructure resilience, performance metrics, and potential harm to consumers of persistently under-provisioned interconnection links. We presenting data in ways that allow us to compare different access providers, and show how congestion varies over time. We focus on seven large U.S. broadband access networks, but there is nothing U.S.-specific about the methods we use. Finally, we describe policy-relevant limitations and implications of the work.
Determining metamodel appropriateness for describing a domain Master Thesis

At ASML, the CARM 2G framework is used to design control systems in the domain of their TWINSCAN lithography platform. In the automotive industry, EAST-ADL is one of the most researched architecture description languages for describing automotive embedded systems. Although CARM 2G and EAST-ADL are targeted at different domains, they both share concepts usable to model features in either domain. These range from hierachical modeling levels describing different levels of refinement, to actual electrical components used within such layers. A different application of EAST-ADL is found in ASML’s Hardware Software Interface. This is a large specification of available software interfaces on a hardware platform, which ASML modeled using the EAST-ADL based tool PREEvision. ASML expressed the desire to learn whether EAST-ADL could be used for modeling the entire TWINSCAN domain, and to evaluate how suited EAST-ADL is for modeling the HSI in. We performed a feasability study to enact whether the EAST-ADL metamodel sufficiently accomodates CARM 2G by re-implementing models of case studies in the EAST-ADL implementation PREEvision. This shows us how the metamodels of both architectures relate, and allowed us to extract a strategy to re-implement arbitrary CARM 2G models in PREEvision. Additionally, we studied the PREEvision implementation of the HSI and identified the shortcomings in this approach. We attempted to alleviate these by employing a custom metamodel specifically targeted at the HSI. We ensured compatibility with PREEvision models by means of a two-step model transformation. In order to quantify the usability and effectiveness of the EAST-ADL metamodel for the CARM 2G and HSI domains, we introduced a novel metric which is able to quantify how well a metamodel fits an arbitrary domain. This confirmed our hypothesis that EAST-ADL does not properly accomodate the CARM 2G domain. Additionally, we found that the custom HSI metamodel we designed forms a better fit for the HSI domain than the PREEvision metamodel does. Determining metamodel appropriateness for describing a domain iii
Working Paper No . 2018-10 Macroeconomic Conditions and Child Schooling in Turkey Pinar Mine Gunes University of Alberta Beyza

This paper examines the effects of macroeconomic shocks on child schooling in Turkey using household labor force surveys from 2005-2013. We use variation in local labor demand as an instrumental variable, particularly regional industry composition and national industry employment growth rates. The results demonstrate that child schooling is pro-cyclical in Turkey, with the most acute effects among children with less educated parents and living in rural areas. Finally, as hypothesized, we find asymmetric effects on child schooling based on skill composition of economic growth. Higher unemployment among unskilled workers increases schooling, whereas higher unemployment among skilled workers decreases schooling.
Family firms and labor demand: Size matters - but only the small ones are different

This paper analyzes the differences in labor demand between family and non-family firms. The majority of firms in modern economies are still family controlled. In addition, these firms seem to exhibit better employment performance than other companies. Therefore, this study estimates a labor demand model with German establishment panel data. Moreover, a Heckman correction is introduced to the regressions to avoid selectivity. The results of random effects and fractional panel probit estimations indicate that own-wage and output elasticities are lower in absolute values, thus supporting the assumption that family firms offer higher job security and are more risk averse than other establishments. However, this result does not hold if the investigation is restricted to establishments with 20 or more employees. There is no evidence of different behavior in larger family firms.
Do Fed Forecast Errors Matter?

There is a large literature evaluating the forecasts of the Federal Reserve by testing their rationality and measuring the size of their forecast errors. There is also a substantial literature and debate on the impact of the Fed’s monetary policy on the economy. We know little, however about the impact of the Fed’s forecast errors on economic outcomes. This paper constructs a measure of a forecast error shock for the Federal Reserve based on the assumption that the Fed follows a forward-looking Taylor rule. Given the effort the Fed puts towards producing forecasts that do not have an endogenous error component, we treat the Fed’s forecast errors as a shock, analogous to a monetary policy shock. Our shock, however, is different in that it is completely unintended by the monetary authority rather than simply unanticipated by the public. We follow Romer and Romer (2004) and investigate the effect of the forecast error shock on output and price movements. Our results suggest that although the absolute magnitude of the forecast error shock is large, the impact of the shock on the macroeconomy is quite small. This finding is robust across a range of different specifications. The maximum impact suggests a decline of less than 0.3 percent of real GDP and less than 0.4 percent of GDP deflator in response to a 100 basis point contractionary forecast error shock.