Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services

Algorithmic decision-making systems are increasingly being adopted by government public service agencies. Researchers, policy experts, and civil rights groups have all voiced concerns that such systems are being deployed without adequate consideration of potential harms, disparate impacts, and public accountability practices. Yet little is known about the concerns of those most likely to be affected by these systems. We report on workshops conducted to learn about the concerns of affected communities in the context of child welfare services. The workshops involved 83 study participants including families involved in the child welfare system, employees of child welfare agencies, and service providers. Our findings indicate that general distrust in the existing system contributes significantly to low comfort in algorithmic decision-making. We identify strategies for improving comfort through greater transparency and improved communication strategies. We discuss the implications of our study for accountable algorithm design for child welfare applications.
Evaluation of Fengyun-3 C Soil Moisture Products Using In situ Data from the Chinese Automatic Soil Moisture Observation Stations : A Case Study in Henan Province , China

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially in crop monitoring and disaster warning. Evaluating the dependability of those products before they can be used on a large scale is crucial. In this study, we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY3C) radiometer against in situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from January 1 to December 31, 2016 in Henan, which is an agricultural province in China. Four statistical parameters were used to evaluate the products’ reliability: mean difference, root-mean-square error (RMSE), unbiased RMSE (ubRMSE), and the correlation coefficient. These statistical indicators revealed that the FY-3C L2 SM product generally did not agree with the in situ SM data from CASMOS. The time-series analysis further indicated that the correlations and estimated error were highly related to the growing periods of the crops in our study area. FY-3C L2 SM data tended to overestimate soil moisture during May, August, and September, when the crops reach their maximum vegetation density, and tended to underestimate the soil moisture content during the rest of the year. The averaged correlation coefficient between FY-3C SM and the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index was 0.55, which demonstrates that the vegetation water content of the crops considerably influences the SM product. To improve the accuracy of the FY-3C SM product, an improved algorithm that can filter out the influences of the crops should be applied in the future.
Systematic Understanding of Mechanism of Yi-Qi-Huo-Xue Decoction Against Intracerebral Hemorrhagic Stroke Using a Network Pharmacology Approach

Background Intracerebral hemorrhage (ICH), a fatal type of stroke, profoundly affects public health. Yi-Qi-Huo-Xue decoction (YQHXD), a traditional Chinese medicine (TCM) prescription, is verified to be an efficient method to treat ICH stroke among the Chinese population. Nevertheless, the pharmacological mechanisms of YQHXD have been unclear. Material/Methods We used a strategy based on network pharmacology to explore the possible multi-component, multi-target, and multi-pathway pattern of YQHXD in treating ICH. First, candidate targets for YQHXD were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Then, these candidate YQHXD targets were used in combination with the known targets for the treatment of ICH stroke to construct the core network (cPPI) using data on protein–protein interaction (PPI). We calculated 5 topological parameters for identification of the main hubs. Pathway enrichment and GO biological process enrichment analyses were performed after the incorporation of the main hubs into ClueGO. Results In total, 55 candidate YQHXD targets for ICH were recognized to be the major hubs in accordance with their topological importance. As suggested by enrichment analysis, the YQHXD targets for ICH were roughly classified into several biological processes (related to redox equilibrium, cell–cell communication, adhesion and collagen biosynthesis, cytokine generation, lymphocyte differentiation and activation, neurocyte apoptosis and development, neuroendocrine system, and vascular development) and related pathways (VEGF, mTOR, NF-kB, RAS/MAPK, JAK/STAT and cytokine–cytokine receptors interaction), indicating those mechanisms underlying the therapeutic effect of YQHXD. Conclusions The present results may serve as a pharmacological framework for TCM studies in the future, helping to promote the use of YQHXD in clinical treatment of ICH.
Immune‐Mobilizing Monoclonal T Cell Receptors Mediate Specific and Rapid Elimination of Hepatitis B–Infected Cells

Therapies for chronic hepatitis B virus (HBV) infection are urgently needed because of viral integration, persistence of viral antigen expression, inadequate HBV‐specific immune responses, and treatment regimens that require lifelong adherence to suppress the virus. Immune mobilizing monoclonal T Cell receptors against virus (ImmTAV) molecules represent a therapeutic strategy combining an affinity‐enhanced T Cell receptor with an anti‐CD3 T Cell‐activating moiety. This bispecific fusion protein redirects T cells to specifically lyse infected cells expressing the target virus‐derived peptides presented by human leukocyte antigen (HLA).
Renin Angiotensin System Inhibitors Reduce Aortic Stiffness and Flow Reversal After a Cryptogenic Stroke

Blood flow reversal is a possible mechanism for retrograde embolism in the setting of high‐risk atherosclerotic plaques in the descending aorta (DAo). Evidence suggests that pulse wave velocity (PWV) is a determinant of blood flow reversal and can be reduced by the destiffening effect of renin‐angiotensin system inhibitors (RASI).
OCCURRENCE OF PHONOLOGICAL ERRORS ACCORDING TO SEVERITY IN CHILDREN WITH SPEECH SOUND DISORDER

(1) Department of Physiotherapy, Communication Science & Disorders, Occupational Therapy, Faculty of Medicine, Universityof São Paulo, São Paulo, SP, Brazil. (2) Department of Physiotherapy, Communication Science & Disorders, Occupational Therapy, Faculty of Medicine, University of São Paulo, São Paulo, SP, Brazil. (3) Department of Physiotherapy, Communication Science & Disorders, Occupational Therapy, Faculty of Medicine, University of São Paulo, São Paulo, SP, Brazil. Conflict of interest: non-existent are the sound substitution, omission or distortion and may occur because an underlying difficulty with the organization of phonological rules and/or auditory perception and/or speech production3,4. The use of simplification of the phonological rules, called phonological processes (PP), is maintained after the expected age of acquisition in children with SSD and sometimes idiosyncratic processes may occur. There are different types of PP that may affect more or less the speech intelligibility5 and involve sound ́s substitution and omission. Distortion is the third type of speech error referred to be a phonetic difficulty characterized by the articulatory imprecision during the production of specific sounds. Distortion does not represent a difficulty with the application of the phonological rules and does not commit the meaning of the words6.  INTRODUCTION
An Expanded Obstetric Comorbidity Scoring System for Predicting Severe Maternal Morbidity.

OBJECTIVE To develop and validate an expanded obstetric comorbidity score for predicting severe maternal morbidity that can be applied consistently across contemporary U.S. patient discharge data sets. METHODS Discharge data from birth hospitalizations in California during 2016-2017 were used to develop the score. The outcomes were severe maternal morbidity, defined using the Centers for Disease Control and Prevention index, and nontransfusion severe maternal morbidity (excluding cases where transfusion was the only indicator of severe maternal morbidity). We selected 27 potential patient-level risk factors for severe maternal morbidity, identified using International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. We used a targeted causal inference approach integrated with machine learning to rank the risk factors based on adjusted risk ratios (aRRs). We used these results to assign scores to each comorbidity, which sum to a single numeric score. We validated the score in California and national data sets and compared the performance to that of a previously developed obstetric comorbidity index. RESULTS Among 919,546 births, the rates of severe maternal morbidity and nontransfusion severe maternal morbidity were 168 and 74 per 10,000 births, respectively. The highest risk comorbidity was placenta accreta spectrum (aRR of 30.5 for severe maternal morbidity and 54.7 for nontransfusion severe maternal morbidity) and the lowest was gestational diabetes mellitus (aRR of 1.06 for severe maternal morbidity and 1.12 for nontransfusion severe maternal morbidity). Normalized scores based on the aRR were developed for each comorbidity, which ranged from 1 to 59 points for severe maternal morbidity and from 1 to 36 points for nontransfusion severe maternal morbidity. The overall performance of the expanded comorbidity scores was good (C-statistics were 0.78 for severe maternal morbidity and 0.84 for nontransfusion severe maternal morbidity in California data and 0.82 and 0.87, respectively, in national data) and improved on prior comorbidity indices developed for obstetric populations. Calibration plots showed good concordance between predicted and actual risks of the outcomes. CONCLUSION We developed and validated an expanded obstetric comorbidity score to improve comparisons of severe maternal morbidity rates across patient populations with different comorbidity case mixes.
ADVANCED TIE FEATURE MATCHING FOR THE REGISTRATION OF MOBILE MAPPING IMAGING DATA AND AERIAL IMAGERY

Abstract. Mobile Mapping’s ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform’s position. Consequently, acquired data products’ positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images’ geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability of putative matches and the utilisation of templates instead of feature descriptors. In our experiments discussed in this paper, typical urban scenes have been used for evaluating the proposed method. Even though no additional outlier removal techniques have been used, our method yields almost 90% of correct correspondences. However, repetitive image patterns may still induce ambiguities which cannot be fully averted by this technique. Hence and besides, possible advancements will be briefly presented.
Single-photon absorption and dynamic control of the exciton energy in a coupled quantum-dot-cavity system

We theoretically investigate the dynamic interaction of a quantum dot in a nanocavity with time-symmetric single-photon pulses. The simulations, based on a wave-function approach, reveal that almost perfect single-photon absorption occurs for quantum-dot-cavity systems operating on the edge between strong- and weak-coupling regimes. The computed maximum absorption probability is close to unity for pulses with a typical length comparable to half of the Rabi period. Furthermore, the dynamic control of the quantum-dot energy via electric fields allows the freezing of the light-matter interaction, leaving the quantum dot in its excited state. Shaping of single-photon wave packets by the electric field control is limited by the occurrence of chirping of the single-photon pulse. This understanding of the interaction of single-photon pulses with the quantum-dot-cavity system provides the basis for the development of advanced protocols for quantum-information processing in the solid state.
Social and economic differentials among households of urban migrants: evidence from Kalutara District, Sri Lanka

Migration to urban areas is a common phenomenon in Sri Lanka since more than three decades. Urban population is gradually increased mainly due to various reasons: socio-economic issues, natural disasters, political and ethnic issues, cultural requirements and improvement in transportation and communication, and migration to urban areas from rural and urban areas. As a result of the migration towards urban areas, socio-economic differences between formal and informal sector households have increased. Therefore, the aim of the study is to explore and estimate the socio-economic differences of urban migrants who are engaged in the formal and informal sector economic activities at the destination. Data was obtained quantitatively from a sample survey by using a face-to-face interview technique, covering 400 migrant households from three urban areas in Kalutara District and qualitative information was gathered using in-depth interview method. The factors related to social and economic differentials of migrant households were analysed by employing descriptive, bivariate and multivariate analyses. Findings of this study revealed that more than half of migrants belong to the reproductive age group. Three fourths of the household heads among migrants are below secondary level education and parents’ aspiration towards the children’s education is quite low, especially in the informal sector. Most of the urban migrants’ employments are at risk because more than two thirds of migrant household heads are engaged in informal economic activities and more than half of households have no economic security of their urban life. According to the bivariate comparison, formal sector employed households differ significantly from informal sector employed households in terms of respondent’s age, resident years at destination, monthly household income, monthly household expenses and Household Assets Index. Furthermore, these differences are enhanced by the multivariate discriminant analysis. Moreover, the qualitative findings discovered that several community and environmental factors such as lack of sanitary facilities and low educational attainment, less awareness and encouragement of employment opportunities have resulted in increasing the negative economic influences within these urban communities. It is suggested that the future employment programs and awareness programs should directly focus on empowering, especially, informal employees and new policies should be introduced to reduce the migration towards urban areas and its negative influences on the destination community.
Learning through an Innovative Formative Assessment Strategy: An Exploratory Study of How Engineering Students Interpret System Equilibrium

Engineering students usually generate diagrams to offload memory and information processing when they design and analyze systems. It is challenging for instructors to provide formative assessment and feedback on their diagrams and systematically and rapidly diagnosing their conceptions of a situation. This study introduces an innovative instructional method, called “pseudo peer diagram” (PPD), where students compare and contrast their work with others as a formative feedback mechanism. Fourteen students who graduated from the First Year Engineering Honors Program were asked to generate free body diagrams to interpret equilibrium in the provided systems. PPDs were presented to enable a direct comparison and to serve a metacognitive function for students who use them as feedback to practice and build up their own self-check strategies. In order to understand how individuals cognitively process PPDs, this study used think-aloud protocol to make students’ cognition explicit. This study revealed several challenges that students encountered when they used free body diagrams to interpret system equilibrium. This study also indicates the effectiveness of PPDs in externalizing students’ understanding of system equilibrium. This research is relevant to engineering instructors and researchers who want to develop students’ abilities to use cognitive strategies effectively. It may also interest engineering instructors who are willing to apply new instructional methods and tools to facilitate students to overcome complex design challenges.
Online Crowd Learning with Heterogeneous Workers via Majority Voting

Many platforms recruit workers through crowd-sourcing to finish online tasks involving a huge amount of effort (e.g., image labeling and content moderation). These platforms aim to incentivize heterogeneous workers to exert effort finishing the tasks and truthfully report their solutions. When the verification for the workers’ solutions is absent, the crowdsourcing problem is challenging and is known as information elicitation without verification (IEWV). Majority voting is a common approach to solve an IEWV problem, where a worker is rewarded based on whether his solution is consistent with the majority. However, most prior related work relies on a strong assumption that workers’ solution accuracy levels are public knowledge. We relax such an assumption and propose an online learning mechanism based on majority voting, which allows the platform to learn the distribution of the workers’ solution accuracy levels. In the mechanism, workers will be asked to report their private accuracy levels (which do not need to be the true values), in addition to deciding their effort levels and solution reporting strategies. The mechanism computes the workers’ rewards based on their reported accuracy levels, and the workers obtain rewards if their reported solutions match the majority. We show that our mechanism induces workers to truthfully report their solution accuracy levels in the long run, in which the platform asymptotically achieves zero regret. Moreover, we show that our online mechanism converges faster when the workers are more capable of solving the tasks.
A Flexible Resistive Pressure Sensor Based on Thermally Expandable Microspheres

flexible pressure sensors, as important parts of electronic skins, have attracted great attention for their great potential applications in soft robot, wearable electronic device and biomedical diagnosis. Pressure sensors based on resistive working mechanisms have attracted more attention owing to their high reliability, facile fabrication techniques and low energy consumption. Recently, great efforts have been focused on increasing the sensitivity of flexible pressure sensors, however, developing high-sensitive pressure sensors with a cost-effective fabrication method are still challenging. In this study, a new type of flexible pressure sensor with great sensitivity of 4.11 kPa-1, fast response time (<35 ms) and high stability (1000 cycles of pressure loading/unloading) has been designed based on thermal expandable microspheres. In addition, the fabricated pressure sensor is successfully applied to detect tiny human motions (deglutition, vocal cord vibration) and monitor finger bending. More importantly, because of the simple fabrication, the flexible pressure sensor can easily achieve large-scale production.
Prioritizing Runtime Verification Violations

Runtime Verification (RV) can help find software bugs by monitoring formally specified properties during testing. A key problem when using RV during testing is how to reduce the manual inspection effort for checking whether property violations are true bugs. To date, there was no automated approach for determining the likelihood that property violations were true bugs to reduce tedious and time-consuming manual inspection.We present RVPRIO, the first automated approach for prioritizing RV violations in order of likelihood of being true bugs. RVPRIO uses machine learning classifiers to prioritize violations. For training, we used a labeled dataset of 1,170 violations from 110 projects. On that dataset, (1) RVPRIO reached 90% of the effectiveness of a theoretically optimal prioritizer that ranks all true bugs at the top of the ranked list, and (2) 88.1% of true bugs were in the top 25% of RVPRIO-ranked violations; 32.7% of true bugs were in the top 10%. RVPRIO was also effective when we applied it to new unlabeled violations, from which we found previously unknown bugs—29 bugs in 7 projects and two bugs in two properties. Our dataset is publicly available online.
Effects of Bacterial Inoculants and Cutting Height on Fermentation Quality of Barley Silage

ABSTRACT This study was conducted to investigate the effects of bacterial inoculation (Lactobacillus plantarum) and cutting height on the chemical composition, fermentation characteristics and in vitro dry matter digestibility (IVDMD) in whole crop barley silage. Barley forage (Youngyang hybrid) was harvested at about 27% of dry matter (DM) level at two different cutting height (5 vs. 15 cm). And it was chopped to 5 cm length and treated with or without L. plantarum. Four replicates of each treatment were ensiled into 10 L mini silo (3 kg) for 100 days. After 100 days, bacterial inoculation decreased(p=0.001) DM content, while increased cutting height increased (p=0.002) DM in uninoculated silage. Crude protein (CP) concentration was decreased by increasing height in uninoculated silage (8.84 vs. 8.16) but increased in inoculated silage (8.19 vs. 8.99). Both neutral detergent fiber (NDF) (p<0.011) and acid detergent fiber (ADF) (p<0.004) were decreased by increasing cutting height of forage at harvest. The IVDMD and ammonia-N was increased (p=0.001) by increasing cutting height and inoculation, respectively. Lactic acid bacteria (LAB) was increased(p=0.002) in inoculated silage, but yeast count was decreased (p=0.026) in uninoculated silages. It is concluded that increased cutting height of forage at harvest could be useful to make a fibrous portion with increase of dry matter digestibility of silages. (