Miracle-dz/UniFAR-FTUs huggingface dataset:
Personalized Stress Detection with Self-supervised Learned Features

Automated stress detection using physiological sensors is challenging due to inaccurate labeling and individual bias in the sensor data. Previous methods consider stress detection as a supervised classiﬁcation task, where bad labeling leads to a large performance drop. Furthermore, the poor generalizability to unseen subjects reveals the importance of personalizing stress detection for both inter-and intra-individual sensor data variability. Towards this end we present a label-free feature extractor and an efﬁcient personalization method with the ”human in the loop” approach. First, we capture the intra-individual variability and encode it in self-supervised learned features, which are usually well separable and independent of noisy stress labels. Next, personalization is achieved by assigning labels to critical reference points via very few interactions between subject and wearable device. The promising results of the conducted experiments show the effectiveness and efﬁciency of our proposed method.
Requirements for extracting ENF data to correctly timestamp a video

—We look at the extraction of Electrical Network Frequency (ENF) data from video. ENF data can be used in timestamping, classically in audio. Recent research has claimed its presence can be detected in video. We especially focus on the properties of complementary metal-oxide-semiconductor (CMOS) sensors and its resulting videos. The CMOS sensor allows for a sampling rate in video that should be high enough to prevent undersampling, and aliasing as a result, when it comes to ENF data. We discuss the properties of a video that should allow for the extraction of ENF although we were not able to conclusively do so ourselves.
USING TIME SERIES OF SENTINEL-1 IMAGES TO PRODUCE DRY BATHYMETRY OF RIVERS

Abstract. A method is presented to produce river cross section profiles from a time series of Sentinel-1 images paired with water level data. Four programs are presented that generate river width data and cross section profiles from SAR or optical images. The programs generate a river bank and island width database with minimum manual intervention. Water level data from in situ stations are interpolated to match the width data and create elevation points from which the cross section profiles are produced. The method is fully described and tested on the Sao Francisco River in Brazil. The width data are plotted against discharge data to compare their progression. Over 1700 cross sections were produced and classified by their shape. Potential and limitations are presented.
Design, synthesis, and cytotoxicity evaluation of new 2,4-disubstituted quinazolines as potential anticancer agents

A series of new 2, 4-disubstituted quinazolines were synthesized by an analog design approach. The synthesis of title compounds (3a–f, 4a–c, 5a–c, and 6a–c) was achieved from the corresponding key intermediates 2-(pyridin3-yl) quinazolin-4(3H)-one(2a), 2-(pyridin-3-yl) quinazolin-4(3H)-one (2b) and 2-(pyrazin-2-yl)quinazolin-4(3H)one (2c) with appropriate amines. The synthesized compounds were characterized by the spectral studies. All the synthesized compounds were evaluated for in vitro anticancer activity employing 3-(4,5-dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide assay against human adenocarcinoma (HT-29), breast cancer (MDA-231), and Ehrlich ascites carcinoma cell lines. Among the tested compounds, 5a has a significant anticancer activity (5.33 μM/ml) against the human adenocarcinoma cell line. Other compounds have shown a moderate anticancer activity against the tested cell lines.
BULK SEGREGANT TRANSCRIPTOME ANALYSIS BASED DIFFERENTIAL EXPRESSION OF DROUGHT RESPONSE GENES IN MAIZE

Plants must overcome various environmental challenges to survive during growth and development. Abiotic stresses like drought, cold, heat and salinity are the major factors having adverse effects on crop production and threat to food security (Zhu, 2016). As a important cereal crop in the world, maize plays crucial role in consolidating world food security (Strable and Scanlon, 2009). However, drought stress is the main limiting factor for production of maize (Gong et al., 2014). During developmental phases, the seedling stage is much more sensitive to dehydration. Severe drought stress causes stunted growth leading to death of maize seedling (Peleg and Blumwald, 2011). Understanding of strategies involved in drought stress responses in maize seedlings, especially the cultivars with excellent drought tolerance, will provide considerable clues to improve the drought tolerance of maize. Phytohormones including abscisic acid (ABA), cytokinin (CK), auxin (IAA), brassinosteriods (BR), salicylic acid (SA) and ethylene (ET) were found involved in drought stress response in plants. Among them, ABA plays central roles in drought stress responses by regulating water loss and adjusting the gene expression (Golldack et al., 2011). The synthesis of ABA rely on catalytic enzymes such as NCED and ABA3/LOS5 (Nambara and Marion-Poll, 2005; Peleg and Blumwald, 2011). In tomato, ABA accumulation and the ability of drought tolerance were significantly increased by overexpressing of LeNCED1 in transgenic plants (Thompson et al., 2007). Similarly, the overexpression of SgNCED1 could enhance the accumulation of ABA in leaves and improve the tolerance to drought stress in tobacco (Zhang et al., 2008). ABA3/LOS5has been modulated for reducing drought damage by overexpressing in transgenic rice (Xiong et al., 2001). During drought stress, induction of transcription factors (TFs) such as AP2/EREBP (APETALA2/ethylene-responsive element binding proteins), bZIP (basic region/leucine zipper motif), NAC (NAM, ATAF and CUC) and MYB (v-myb avian myeloblastosis viral oncogene homolog) regulates the expression of down stream genes and enhances tolerance to abiotic stresses in plants. For example, the expression levels of transcription factors MYBJ7, BZIP50, C2H2and NAC2increasedafter imposition of drought stress in soybean roots (Pereira et al., 2011). Overexpression of the gene SNAC2 enhanced the ability of drought tolerance in rice (Hu et al., 2008). Tolerance to drought was enhanced by overexpressing the maize transcription factor ZmMYB3R in transgenic Arabidopsis (Wu et al., 2019). Transcription factors are an important molecular mechanism for plants to Pak. J. Agri. Sci., Vol. 57(4), 909-923; 2020 ISSN (Print) 0552-9034, ISSN (Online) 2076-0906 DOI: 10.21162/PAKJAS/20.9899 http://www.pakjas. com.pk
Comparative study on different walking load models

Since the 1970s, researchers have proposed many human walking load models, and some of them have even been adopted by major design guidelines. Despite their wide applications in structural vibration serviceability problems, the difference between these models in predicting structural responses is not clear. This paper collects thirteen popular walking load models and compares their effects on structure’s responses when subjected to human walking load. Model parameters are first compared among all the models including orders of the model, dynamic load factors, phase angles and initial load. The responses of a single-degree-of-freedom system with various natural frequencies and damping ratios to the thirteen load models are then calculated and compared in terms of peak values and root mean square values. It is found that the difference among all the models are significant, indicating that a proper walking load model is crucial for the structure’s vibration serviceability assessment.
Digital Implementation of a Spiking Convolutional Neural Network for Tumor Detection

: The structural variation of the brain tissue creates challenges for detection of tumors in MRI images. In this paper, an architecture for spiking convolutional neural networks (SCNNs) is implemented in an embedded system and their potential is evaluated in terms of hardware utilization and power consumption in complex applications such as tumor detection. Accordingly, the structure of the proposed SCNN is implemented on a field-programmable gate array (FPGA) using fixed point arithmetic. To evaluate the speed, accuracy and flexibility of the proposed SCNN, Izhikevich neuron model is used with the spike-timing-dependent plasticity (STDP) learning rule. The suggested neural network is explored for digital implementation possibility and costs. Results of the hardware synthesis and digital implementation are presented on an FPGA.
Advantages of robotic right colectomy over laparoscopic right colectomy beyond the learning curve: a systematic review and meta-analysis

Department of Digestive and Hepatobiliary Surgery, Henri Mondor University Hospital, Créteil, France Contributions: (I) Conception and design: All authors; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: L Lauka, N Beghdadi; (V) Data analysis and interpretation: L Lauka, N Beghdadi, N de’Angelis; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. Correspondence to: Nicola de’Angelis, MD, PhD. Department CARE, Unit of Digestive and Hepato-Pancreato-Biliary Surgery, Henri Mondor Hospital, AP-HP, University of Paris Est, UPEC, 51 Avenue du Maréchal de Lattre de Tassigny, 94010, Créteil, France. Email: nicola.deangelis@aphp.fr.
An efficient perturbation theory of density matrix renormalization group

Emanuele Tirrito,1 Shi-Ju Ran,1 Andrew J. Ferris,1 Ian P. McCulloch,2 and Maciej Lewenstein1, 3 ICFO Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain Centre for Engineered Quantum Systems, School of Physical Sciences, The University of Queensland, Brisbane, Queensland 4072, Australia ICREA Institució Catalana de Recerca i Estudis Avançats, Lluis Companys 23, 08010 Barcelona, Spain
No . 2017-01 Dissimilarity on the Career Path : The Occupational Structure of the American Indian / Alaska Native Workforce

We analyze the occupational structure of the non-Hispanic American Indian/Alaska Native (AIAN) workforce in the United States, relative to the non-Hispanic White workforce, using public-use census microdata. AIAN workers are generally overrepresented in low-skilled occupations and underrepresented in high-skilled occupations, relative to White workers. This pattern is stronger among men than among women and stronger among single-race AIANs than multiple-race AIANs. AIAN occupational dissimilarity does not appear to have declined substantially since 1980. Controlling for individual differences in factors such as education, age, location, and language proficiency accounts for a significant proportion of AIAN underrepresentation in high-education occupations.
Ocean Current Turbine Power Maximization: A Spatiotemporal Optimization Approach

This paper presents a novel spatiotemporal optimization approach for maximizing the output power of an ocean current turbine (OCT) under uncertain ocean velocities. In order to determine output power, ocean velocities and the power consumed and generated by an OCT system are modeled. The stochastic behavior of ocean velocities is a function of time and location, which is modeled as a Gaussian process. The power of the OCT system is composed of three parts, including generated power, power for maintaining the system at an operating depth, and power consumed for changing the water depth to reach the maximum power. Two different algorithms, including model predictive control (MPC) as a model-based method and reinforcement learning (RL) as a learning-based method, are proposed to design the optimization structure, and comparative studies are presented. On one hand, the MPC based controller is faster in finding the optimal water depth, while the RL is also computationally feasible considering the required time for changing operating depth. On the other hand, the cumulative energy production of the RL algorithm is higher than the MPC method, which verifies that the learning-based RL algorithm can provide a better solution to address the uncertainties in renewable energy systems. Results verify the efficiency of both presented methods in maximizing the total power of an OCT system, where the total harnessed energy after 200 hours shows an over 18% increase compared to the baseline.
Autologous breast reconstruction beyond the DIEP: a narrative review of autologous breast reconstruction options beyond the DIEP flap

The field of breast reconstruction has undergone tremendous advancement over the years both in terms of prosthesis-based reconstruction as well as autologous breast reconstruction. In the modern era, the abdomen represents the most commonly used donor site for autologous breast reconstruction. The traditional transverse rectus abdominis myocutaneous (TRAM) flap has been gradually replaced with musclesparing flaps of the abdominal musculature in hopes of minimizing donor site morbidity. The muscle-sparing TRAM, deep inferior epigastric perforator (DIEP) flap, and superficial inferior epigastric artery (SIEA) flap have gained in popularity, with the DIEP representing the gold standard in autologous microvascular breast reconstruction. However, in certain circumstances a traditional DIEP may not be possible, and modifications and alternate donor sites have to be considered. The goals pursued by any breast reconstruction should consider the following aspects: symmetry, shape, ptosis, natural movement, softness and sensitivity. This review aims to discuss the evolution and innovation in the abdominal donor site as well as to introduce alternate donor sites that can be used for free tissue breast reconstruction. Our purpose is to analyze the various alternative options that can be used in breast reconstruction considering the advantages and the disadvantages of each flap. This review can help plastic surgeons to construct an algorithm for choosing the appropriate alternative free flap for breast reconstruction when the DIEP flap is not available.
A Tutorial on the Computation of Bayes Factors

8 In this review paper we revisit several of the existing schemes that approx9 imate predictive densities and, consequently, Bayes factors. We also present 10 the reversible jump MCMC scheme, which can be thought of as an MCMC 11 scheme over the space of models. These approaches are applied to select the 12 number of common factors in the basic normal linear factor model, which is a 13 high profile example within the psychometrics community. 14
The Relationship Between Workplace Environment, Teacher Well-Being, and Young Children’s Behavioral Outcomes

Early childhood educators are asked to provide a nurturing, high-quality learning environment which will support positive developmental outcomes for all children. However, when teachers are not provided with adequate workplace support or training, this can have deleterious effects on their psychological well-being and the way they interact with the children in their care. As a result of teachers feeling overwhelmed and stressed, children’s development may be negatively impacted. Purpose: Using Urie Bronfenbrenner’s bioecological model of human development as a theoretical framework, this study investigated the relationship between workplace environment, teachers’ psychological well-being, and children’s behavioral outcomes. Objective. There are three primary goals of this paper: (1) to analyze the prevalence of depressive symptoms reported by Head Start teachers across gender; (2) to understand the relationship between workplace supports and experiences of depression among Head Start teachers; and (3) to examine the influence of workplace supports or classroom environment and teachers’ depression on children’s behavioral outcomes. Methods. Several correlations and multiple linear regression analyses were conducted in this study using data from the 2014 Head Start Family and Child Experiences Survey (FACES) to answer specific research questions. Measures included classroom observation and teacher and center director surveys. Discussion. Findings from this paper will begin to fill the existing gap in the research literature connecting workplace environments, teacher well-being, and children’s developmental outcomes. Future directions and implications for policy within the early childhood profession are discussed.
Role of secondary metabolites biosynthesis in resistance to cotton leaf curl virus (CLCuV) disease

Disease percentage on six cotton varieties with respect to time for cotton leaf curl virus (CLCuV) was evaluated. In August 2007, the maximum disease was observed in CIM-506, CYTO-89 and BH-118 (susceptible), whereas CIM-443 was resistant with lower disease percentage. It was found that the leaf area, fresh weight and dry weight were more in healthy sample of leaves as compared to diseased samples of same varieties. Maximum leaf area was observed in BH-118 in healthy sample as compared to diseased ones and minimum leaf area was observed in CYTO-89. Maximum fresh weight and dry weight were present in NIAB-111 and CIM-443 in healthy sample as compared to diseased sample, respectively. Secondary metabolites production in healthy and diseased sample of leaves of cotton varieties after the attack of CLCuV found maximum phenolics, carotenoids, chlorophyll a, chlorophyll b and total chlorophyll a and b in healthy sample and minimum contents present in diseased sample. CIM-446 was the best variety to resist the cotton leaf curl disease. CIM-446 had maximum chlorophyll contents as compared to diseased leaves, and maximum phenolics were present in BH-118 and carotenoids in NIAB-111 in healthy sample in resistance to CLCuV. So, CIM-446, CIM-443, NIAB-111 and BH-118 were the best varieties in resistance to cotton leaf curl disease. The productions of secondary metabolites were high in healthy leaves in resistance to cotton leaf curl disease. Key words: Cotton varieties, cotton leaf curl disease percentage, leaf area, fresh and dry weight, chlorophyll a, b, a + b, carotenoids, phenolics.
Galaxy and cluster biasing from Local Group dynamics

Comparing the gravitational acceleration induced on the Local Group of galaxies by different tracers of the underline density field we estimate, within the linear gravitational instability theory and the linear biasing ansatz, their relative bias factors. Using optical SSRS2 galaxies, IRAS (PSCz) galaxies and Abell/ACO clusters, we find bO,I � 1.21 ± 0.06 and bC,I � 4.3 ± 0.8, in agreement with other recent studies. Finally, there is an excellent one-to-one correspondence of the PSCz and Abell/ACO cluster dipole profiles, once the latter is rescaled by bC,I, out to at least � 150 h 1 Mpc.
Automatic Identification and Precise Attribution of DRAM Bandwidth Contention

The limited DRAM bandwidth of today’s computing systems is a bottleneck for many applications. But the identification of DRAM bandwidth contention in applications is difficult. The measured bandwidth consumption of an application can not identify bandwidth contention. In theory, NUMA systems can provide higher memory bandwidth. But applications often make poor use of the resources. To address these challenges, we introduce a novel method to identify DRAM bandwidth contention and bad usage of NUMA resources. It consists of metrics to judge the severity of bandwidth contention and the degree of imbalanced resource usage in NUMA systems. Our tool can automatically scan an application for DRAM contention problems. Together with the precise location of the origin, intuitive optimization guidance is given. This approach for finding DRAM contention is based on the memory access latency. By comparing the experienced latency of an application with the uncontended hardware latency, we can find the contention. Hardware instruction sampling enables precise identification of the origin. It also provides information about accessed memories, which we use to calculate a NUMA imbalance metric. In a detailed evaluation with several micro-benchmarks, we show that our new method does indeed quantify the severity of DRAM contention beyond the possibilities of simple bandwidth consumption measurement and existing tools. We also apply our approach to real applications and confirm that it gives useful optimization advice to users.
Selective Coflow Completion for Time-sensitive Distributed Applications with Poco

Recently, the abstraction of coflow is introduced to capture the collective data transmission patterns among modern distributed data-parallel application. During processing, coflows generally act as barriers; accordingly, time-sensitive applications prefer their coflows to complete within deadlines and deadline-aware coflow scheduling becomes very crucial. Regarding these data-parallel applications, we notice that many of them, including large-scale query system, distributed iterative training, and erasure codes enabled storage, are able to tolerate loss-bounded incomplete inputs by design. This tolerance indeed brings a flexible design space for the schedule of their coflows: when getting overloaded, the network can trade coflow completeness for timeliness, and balance the completenesses of different coflows on demand. Unfortunately, existing coflow schedulers neglect this tolerance, resulting in inflexible and inefficient bandwidth allocations. In this paper, we explore this fundamental trade-off and design Poco, a POlicy-based COflow scheduler, to achieve customizable selective coflow completions for these emerging time-sensitive distributed applications. Internally, Poco employs a suite of novel designs along with admission controls to make flexible, work-conserving, and performance-guaranteed rate allocation to online coflow requests very efficiently. Extensive trace-based simulations indicate that Poco is highly flexible and achieves optimal coflow schedules respecting the requirements specified by applications.
From Clinical Trial to Clinical Practice: Assessing the External Validity of Endovascular Treatment in Acute Ischemic Stroke

Background: Endovascular treatment (EVT) for acute ischemic stroke is guided by clinical trials assumed to have high external validity. To our knowledge, this assumption has not been rigorously examined. Methods: Patients from two U.S. academic comprehensive stroke centers receiving endovascular treatment for acute ischemic stroke were retrospectively reviewed from January 2012 through December 2016. Clinical characteristics, treatment times, neuroimaging findings, and functional outcomes were compared to data from the pragmatic EVT trial, MR CLEAN. External validity was assessed quantitatively and qualitatively. Results: 236 patients presenting with anterior circulation large vessel occlusion were included. 63% (148/236) would have met criteria for MR CLEAN; the primary reason for exclusion would have been a time from symptom onset to groin puncture greater than 6 hours. Ordinal shift analysis of 90 day modified Rankin scale (mRS) of our clinical practice did not differ from the intervention arm of MR CLEAN, (p=0.26). Favorable outcome (mRS 0-2) occurred in 35% of our combined practice and in 33% of the trial intervention arm (p=0.63). The rates of hemicraniectomy (3% vs. 6% p=0.09) and PH-2 type symptomatic intracerebral hemorrhage (5.1% vs. 6.0% p=0.55) did not differ between the two groups. Conclusion: Our clinical experience was comparable to MRCLEAN, supporting the external validity of this trial to clinical practice. We treated patients who would have been excluded from this trial because of a longer time to groin puncture. Satisfactory results can be obtained with endovascular treatment, even when treating patients beyond 6 hours from symptom onset.