Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect Of Work Motivation On The Performance Of Employees Of The Regional Public Service Agency For The Drinking Water Supply System Of The Public Works And Spatial Planning Service Of East Nusa Tenggara Province

Low employee performance and its relation with extrinsic and extrinsic work motivation have been the focus of this study. The study examines how extrinsic and intrinsic motivation partially and simultaneously affect the performance of employees at the Regional Public Service Agency for the Drinking Water Supply System of the Public Works and Spatial Planning Service (Badan Layanan Umum Daerah Sistem Penyediaan Air Minum Dinas Pekerjaan Umum dan Penataan Ruang - BLUD SPAM of DPUPR) of East Nusa Tenggara Province. This study was quantitative, with a cross-sectional approach from September to November 2020. The population was 38 employees, and the sample consisted of 33 people determined purposively by considering their willingness to be respondents. We used a questionnaire as the instrument, and data were analyzed using descriptive statistical analysis and simple and multiple linear regression analysis. The results show that extrinsic motivation, including incentives, working conditions, work relationships between leaders and staff, and job security, partially affects employee performance. Intrinsic motivation, including the work itself, responsibility, work knowledge, and work performance, partially influences employee performance. Extrinsic and intrinsic motivation simultaneously influence employee performance. It can be concluded that there is a positive and significant influence between extrinsic and intrinsic motivation partially and simultaneously on the performance of employees of the Regional Public Service Agency for the Drinking Water Supply System of the Public Works and Spatial Planning Service (Badan Layanan Umum Daerah Sistem Penyediaan Air Minum Dinas Pekerjaan Umum dan Penataan Ruang - BLUD SPAM of DPUPR) of East Nusa Tenggara Province.
Filament Depolymerization Can Explain Chromosome Pulling during Bacterial Mitosis

Chromosome segregation is fundamental to all cells, but the force-generating mechanisms underlying chromosome translocation in bacteria remain mysterious. Caulobacter crescentus utilizes a depolymerization-driven process in which a ParA protein structure elongates from the new cell pole, binds to a ParB-decorated chromosome, and then retracts via disassembly, pulling the chromosome across the cell. This poses the question of how a depolymerizing structure can robustly pull the chromosome that disassembles it. We perform Brownian dynamics simulations with a simple, physically consistent model of the ParABS system. The simulations suggest that the mechanism of translocation is “self-diffusiophoretic”: by disassembling ParA, ParB generates a ParA concentration gradient so that the ParA concentration is higher in front of the chromosome than behind it. Since the chromosome is attracted to ParA via ParB, it moves up the ParA gradient and across the cell. We find that translocation is most robust when ParB binds side-on to ParA filaments. In this case, robust translocation occurs over a wide parameter range and is controlled by a single dimensionless quantity: the product of the rate of ParA disassembly and a characteristic relaxation time of the chromosome. This time scale measures the time it takes for the chromosome to recover its average shape after it is has been pulled. Our results suggest explanations for observed phenomena such as segregation failure, filament-length-dependent translocation velocity, and chromosomal compaction.
Assessing Trade-Offs between Stealthiness and Node Recruitment Rates in Peer-to-Peer Botnets

Botnets denote collections of compromised computers under adversary control and, although early botnets using centralized command and control (C&C) structures were fairly easily defeated, botnets remain a serious global security threat. in part, this is due to the evolution within the adversarial communities using highly diffuse decentralized peer-to-peer (P2P) based C&C within modern botnets, which has proven far more difficult to address. the resulting increased botnet resilience though comes at the cost of placing the bots further from the botmasterâs direct control, thereby, increasing the time required to recruit subsets of bots to specific malicious tasks, (i.e., to send spam, engage in a DDOS attack, etc.). This work explores the specific tradeoffs that occur between achievable bot recruitment rates and overall botnet stealthiness within P2P structured botnets. It is shown that rapid recruitment of nodes (or bots) leads directly to an order of magnitude increase in the botnetâs generated network traffic, which makes the botnet significantly more visible (and susceptible) to defensive counter-measures. Kademlia is used through out this work as the exemplar P2P protocol as, within the real-world, Kademlia has proven to provide an effective C&C mechanism for a number of the longer-lived botnets.
Solving a Nonlinear Fractional Integral Equation by Fixed Point Approaches Using Auxiliary Functions Under Measure of Noncompactness

This manuscript is devoted to ensure the existence of a solution to nonlinear fractional integral equations with three variables under a measure of noncompactness. In order to accomplish our main goal, we develop a new fixed point theorem that generalizes Darbo’s fixed point theorem by utilizing a measure of noncompactness and a new contraction operator. A related tripled FP theorem is also obtained. Finally, we use this generalized Darbo’s fixed point theorem to solve a nonlinear fractional integral equation involving three variables, and an example to demonstrate our results is presented.
The interannual sea level variability in the Indian Ocean as simulated by an Ocean General Circulation Model

Limited coverage of tide gauge observations and limited length record of altimeter observations remain inadequate for the Indian Ocean sea level variability studies especially for longer periods. This study takes advantage of Ocean General Circulation Model (OGCM) simulations and ocean reanalysis to explore the interannual variability of sea level in the Indian Ocean. The model simulated sea level anomalies display good correlation with altimetry and reanalysis products. This consistency in model simulations with observations and reanalysis highlights the potential use of this OGCM in understanding the sea level variability. Analysis reveals that co‐occurrence years (years when Indian Ocean Dipole (IOD) and El Niño events co‐occur) contribute significantly towards the interannual variability in the Indian Ocean compared to pure IOD or El Niño events, and are characterized by persistent generation of open ocean downwelling, with maximum signals in the 10° to 5°S region. The OGCM experiments are carried out by modulating the forcing fields over the Pacific and the Indian Ocean to understand the physical mechanisms causing sea level variability. The experiments suggest that the remote forcing from the Pacific Ocean via Indonesian ThroughFlow (ITF) induce significant sea level changes in the southern Indian Ocean only with variability mostly in the decadal time scales and the northern and equatorial Indian Ocean are not affected by ITF. This study also shows that El Niño and IOD‐induced variations in zonal wind stress and wind stress curl mainly contribute the interannual sea level variations in the Indian Ocean. The forcing associated with the co‐occurrence years are multi‐phased with coastal and open ocean forcing. Whereas the pure IOD and El Nino forcing is mainly found only over the open ocean. The decadal variability in the ENSO is primarily responsible for the decadal sea level variability in the Indian Ocean by modulating ITF transport.
Splenic diffuse red pulp small B-cell lymphoma: revision of a series of cases reveals characteristic clinico-pathological features

Background Splenic diffuse red pulp small B-cell lymphoma is an uncommon B-cell lymphoma, now recognized as a provisional entity in the 2008 update of the WHO Classification. Additional work is required to review this entity and establish its diagnostic features. Design and Methods We have retrospectively analyzed the disease features in a highly selected series of 17 patients diagnosed as splenic diffuse red pulp small B-cell lymphoma. Results The median age was 65.5 years (range 40–79 years) and there was a predominance of males (male/female ratio: 2.4). Clinical manifestations were mainly derived from splenomegaly. Splenectomy was the front-line treatment in 11 symptomatic patients; the remaining 6 received chemotherapy initially followed by splenectomy. After a mean follow-up of 72 months, the five-year overall survival was 93%. All cases showed a purely diffuse pattern of splenic infiltration by monomorphous small cells with small round nuclei and pale cytoplasm. All bone marrow biopsies showed tumoral infiltration, with intrasinusoidal infiltration. Peripheral blood cells were small to medium-sized, with clumped chromatin and round nuclear outline and villous cytoplasm. Neoplastic cells had a CD20+, CD23−, bcl6−, Annexin A1- phenotype, with frequent expression of DBA44+ (15/17) and IgG (10/15). FCM data had a B-cell phenotype (CD19+, CD20+, CD22+) with FMC7 (10/11) and CD11c (5/8) expression. Clonal IgH rearrangement studies in 4 cases showed IgVH mutations in all cases, without VH1.2 usage. Conclusions Our data suggest that splenic diffuse red pulp small B-cell lymphoma is a distinct entity with morphological and immunophenotypical features that differ from those of other splenic lymphomas.
Comparative experiments with a new adaptive controller for robot arms

An adaptive controller is discussed and a proof of its global asymptotic stability with respect to the standard rigid body model of robot arm dynamics is presented. Experimental data from a study of this and other globally asymptotically stable adaptive controllers on two very different robot arms are used to reconcile several previous contrasting empirical studies, demonstrate and compare their superior tracking performance, and examine contexts that compromise their advantage. <<ETX>>
Anomaly Detection in Time Series of Graphs using Fusion of Graph Invariants

Given a time series of graphs <i>G</i>(<i>t</i>)=(<i>V</i>,<i>E</i>(<i>t</i>)) , <i>t</i>=1,2,. , where the fixed vertex set <i>V</i> represents “actors” and an edge between vertex <i>u</i> and vertex <i>v</i> at time <i>t</i>(<i>uv</i> ∈ <i>E</i>(<i>t</i>)) represents the existence of a communications event between actors <i>u</i> and <i>v</i> during the <i>t</i><sup>th</sup> time period, we wish to detect anomalies and/or change points. We consider a collection of graph features, or invariants, and demonstrate that adaptive fusion provides superior inferential efficacy compared to naive equal weighting for a certain class of anomaly detection problems. Simulation results using a latent process model for time series of graphs, as well as illustrative experimental results for a time series of graphs derived from the Enron email data, show that a fusion statistic can provide superior inference compared to individual invariants alone. These results also demonstrate that an adaptive weighting scheme for fusion of invariants performs better than naive equal weighting.
Quality Enhancement Based Video Captioning in Video Communication Systems

Video captioning is an automatic task that collects natural language to represent visual content. Recently, it has achieved lots of amazing progress thanks to deep learning techniques. Most techniques have mainly focused on a deep learning network architecture, whereas video quality and resolution have not been fully considered, although their impact on captioning performance is very strong. Since video communication systems usually perform compression, original quality and resolution can be degraded and down-sampled for significant reduction of the data size, which results in severe quality degradation. Hence, this paper analyzes the impact of the compression and the down-sampling on the captioning, and proposes a quality enhancement method for the video captioning. First, the proposed method performs quality classification to investigate the quality of each frame. Next, super-resolution (SR) is used to enhance the frames in terms of their quality and resolution. Finally, a video captioning network uses the enhanced frames to generate accurate sentences. Experimental results show that the proposed method drastically improves the captioning performance, when both quality and resolution of input videos are randomly determined.
Optimal Sensing Strategies for Mobile Robot Formations: Resource-Constrained Localization

This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors’ bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed at each time step. The localization uncertainty of the group, determined by the covariance matrix of the equivalent continuous-time system at steady state, is expressed as a function of the sensor measurements’ frequencies. The trace of the submatrix corresponding to the position estimates is selected as the optimization criterion, under linear constraints on the measuring frequency of each sensor and the cumulative rate of EKF updates. This formulation leads to a convex optimization problem whose solution provides the sensing frequencies, for each sensor on every robot, required in order to maximize the positioning accuracy for the group. Simulation experiments are presented that demonstrate the applicability of this method and provide insight into the properties of the resource-constrained cooperative localization problem.
Use of a dialyzable short-chain phospholipid for efficient preparation of virosome vaccines against Newcastle disease

Virosomes can be regarded as liposomes carrying the spike proteins of enveloped virus on their surface. To further advance the use of virosomes, we developed a solubilization/ reconstitution procedure for construction of Newcastle disease (ND)-virosomes, which would be easily applicable to industrial production. This procedure included the use of 1,2-dihexanoylphosphatidylcholine (DHPC) as a viral membrane solubilizer. DHPC is a short-chain phospholipid with detergent-like property and with a relatively high critical micelle concentration (CMC, 14 mM). Virosomes were prepared by solubilization of virus with DHPC followed by the removal of nucleocapsids by ultracentrifugation. The solubilized membrane components were then easily reconstituted by the dialysis removal of DHPC. Biochemical analysis revealed that ND-virosomes contained both hemagglutinin-neuraminidase (HN) and fusion (F) proteins, with preserved biological activity. The immunogenicity of ND-virosomes was determined in chickens after subcutaneous immunization. The relatively high hemagglutination-inhibition (HI) antibody titers and high clinical protection upon viral challenge were found in animals that received ND-virosomes. Using DHPC for the production of virosomes was uncomplicated and would allow further exploitation of virosomes as subunit-vaccines not only in an academic field, but also in an industrial setting.
Higher bandwidth may sometimes reduce cloud application performance

Cloud computing has experienced explosive growth in last ten years. Since cloud applications usually come up with large amounts of data transfer, the network capability becomes one of the dominant performance factors. Judging from common sense, it seems obvious that the higher quantity of bandwidth guaranteed for a job, the higher performance we will achieve. Rather, in this paper, we found that the effect of providing higher bandwidth guarantee turns to be uncertain. Without efficient work and flow scheduling mechanism, merely increasing the bandwidth allocated for the job may actually be as harmful as reducing the bandwidth.
Competitive Inhibitions of the Chlorophyll Synthase of Synechocystis sp. Strain PCC 6803 by Bacteriochlorophyllide a and the Bacteriochlorophyll Synthase of Rhodobacter sphaeroides by Chlorophyllide a

ABSTRACT The photosynthetic growth of Synechocystis sp. strain PCC 6803 is hampered by exogenously added bacteriochlorophyllide a (Bchlide a) in a dose-dependent manner. The growth inhibition caused by Bchlide a, however, is relieved by an increased level of exogenously added chlorophyllide a (Chlide a). The results are explained by the competitive inhibition of chlorophyll synthase by Bchlide a, with inhibition constants (K Is) of 0.3 mM and 1.14 mM in the presence of sufficient geranylgeranyl pyrophosphate (GGPP) and phytyl pyrophosphate (PPP), respectively. Surprisingly, the bacteriochlorophyll synthase of Rhodobacter sphaeroides is inhibited competitively by Chlide a, with K Is of 0.54 mM and 0.77 mM in the presence of sufficient GGPP and PPP, respectively. Consistently, exogenously added Chlide a inhibits the metabolic conversion of exogenously added Bchlide a to bacteriochlorophyll a by an R. sphaeroides bchFNB-bchZ mutant that neither synthesizes nor metabolizes Chlide a. The metabolic inhibition by Chlide a, however, is relieved by the elevated level of Bchlide a. Thus, the chlorophyll synthase of Synechocystis sp. PCC 6803 and the bacteriochlorophyll synthase of R. sphaeroides, both of which perform ping-pong-type reactions, are inhibited by Bchlide a and Chlide a, respectively. Although neither inhibitor is catalyzed by the target enzyme, inhibitions in the competitive mode suggest a structural similarity between their active sites.
A Survey on Video-based Vehicle Behavior Analysis Algorithms

Analysis of the Vehicle Behavior is mainly to analyze and identify the vehicles’ motion pattern, and describe it by the use of natural language. It is a considerable challenge to analyze and describe the vehicles’ behavior in a complex scene. This paper first hackles the development history of the intelligent transportation system and analysis of vehicles’ behavior, and then conducts an in-depth analysis of current situation of vehicle behavior analysis from the video processing, video analysis and video understanding, summarizes the achieved results and the key technical problems, and prospects the future development of vehicle behavior analysis.
Effect of route diversity by employing turbo coding in multihop ad hoc and mesh networks

Sensor networks have attracted enormous attention in recent years. These networks can form a multiroute multihop structure by the signal relaying via multiple sensor nodes. When the signals are transmitted over multiple routes, route diversity effect becomes possible. This effect can help in preventing performance degradation caused by the quality loss of each route. Forward Error Correction (FEC) schemes and turbo coding can be expected to enhance the route diversity. A turbo encoder generates one message stream and two parity streams whilst the message stream is influential for decoding process rather than the parity streams. Thus by allocating the message stream to a reliable route, the performance degradation could be prevented. In this paper, we examine the effect of the route diversity in multihop networks using turbo codes. The diversity effect against the quality loss of the multiple routes is investigated. We adopt the triangle mesh networks for the evaluation. The results suggest that the multiroute transmissions have high diversity effect. They also suggest that large performance degradation can be prevented by appropriate route assignment of the streams even though the link quality of the multiple routes cannot be guaranteed.
Oxytocin Attenuates Stress-Induced c-fos mRNA Expression in Specific Forebrain Regions Associated with Modulation of Hypothalamo–Pituitary–Adrenal Activity

We reported previously that the neuropeptide oxytocin attenuates stress-induced hypothalamo–pituitary–adrenal (HPA) activity and anxiety behavior. This study sought to identify forebrain target sites through which oxytocin may mediate its anti-stress effects. Ovariectomized, estradiol-treated rats received intracerebroventricular infusions of oxytocin (1 or 10 ng/hr) or vasopressin (10 ng/hr), and the patterns of neuronal activation after restraint stress were determined by semiquantitative mapping of c-fos mRNA expression. Oxytocin administration significantly attenuated the release of ACTH and corticosterone and the increase in corticotropin-releasing factor mRNA expression in the hypothalamic paraventricular nucleus (PVN) in response to 30 min restraint. Restraint also induced the expression of c-fos mRNA in selective regions of the forebrain, including the PVN, paraventricular thalamic nucleus, habenula, medial amygdala, ventrolateral septum (LSV), most subfields of the dorsal and ventral hippocampus, and piriform and endopiriform cortices. In most cases, this level of gene expression was unaffected by concomitant administration of oxytocin. However, in the PVN, LSV, and throughout all subfields of the dorsal hippocampus, restraint evoked no detectable increase in c-fos mRNA in animals treated with either dose of oxytocin. Vasopressin had no effects on either HPA axis responses or neuronal activation in response to restraint, indicating that the effects were highly peptide selective. These data show that central oxytocin attenuates both the stress-induced neuroendocrine and molecular responses of the HPA axis and that the dorsal hippocampus, LSV, and PVN constitute an oxytocin-sensitive forebrain stress circuit.
Gaussian Mixture Models For Robust Unsupervised Scanning-Electron Microscopy Image Segmentation Of North Sea Chalk

Scanning-Electron images from North Sea Chalk are studied for important rock properties. To relieve this manual labor, we investigated several standard image processing methods that underperformed on complicated chalk. Due to the lack of manually labeled data, deep neural networks could not be adequately applied. Gaussian Mixture Models learnt a two-fold representation that separated the background well from the rock. Subsequent morphological filtering cleans up the prediction and enables automatic analysis.
LIVE: Lightweight Integrity Verification and Content Access Control for Named Data Networking

Named data networking (NDN) is a new paradigm for the future Internet wherein interest and data packets carry content names rather than the current IP paradigm of source and destination addresses. Security is built into NDN by embedding a public key signature in each data packet to enable verification of authenticity and integrity of the content. However, existing heavyweight signature generation and verification algorithms prevent universal integrity verification among NDN nodes, which may result in content pollution and denial of service attacks. Furthermore, caching and location-independent content access disables the capability of a content provider to control content access, e.g., who can cache a content and which end user or device can access it. We propose a lightweight integrity verification (LIVE) architecture, an extension to the NDN protocol, to address these two issues seamlessly. LIVE enables universal content signature verification in NDN with lightweight signature generation and verification algorithms. Furthermore, it allows a content provider to control content access in NDN nodes by selectively distributing integrity verification tokens to authorized nodes. We evaluate the effectiveness of LIVE with open source CCNx project. Our paper shows that LIVE only incurs average 10% delay in accessing contents. Compared with traditional public key signature schemes, the verification delay is reduced by over 20 times in LIVE.