Miracle-dz/UniFAR-FTUs huggingface dataset:
An Assessment of Service Delivery Plans Submitted to the Texas Department of Housing and Community Affairs for the Comprehensive Energy Assistance Program

An Assessment of Service Delivery Plans Submitted To The Texas Department of Housing and Community Affairs For The Comprehensive Energy Assistance Program. The paper begins by discussing issues related to poverty including the definition of poverty, the nature and causes of poverty, the effects of poverty, and the public perceptions about the poor. The discussion then focuses on recent changes to welfare legislation particularly those resulting from the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996. The paper then focuses on general issues related to program planning and then turns to a discussion of the Comprehensive Energy Assistance Program (CEAP), a program designed to address the issue of poverty and administered by a state agency, the Texas Department of Housing and Community Affairs (TDHCA). The conceptual framework for the research is developed from the requirements of the Service Delivery Plan (SDP) for CEAP, issued by TDHCA. Service delivery plans submitted for Fiscal Year 1999 and 2000 are analyzed to see if they conform to tho requirements promulgated by the department. The methodology and results of the research are described in the latter half of the paper. Results show that the majority of SDPs submitted to TDHCA for CEAP do not have all the required elements. Recommendations are, therefore, developed in response to the results.
Automated Segmentation of Common Carotid Artery in Ultrasound Images

We propose a basis splines-based based active contour method for the segmentation of lumen boundary and media adventitia boundary from transverse and longitudinal B-mode ultrasound images. Basis-spline has M knots in the shape template and five free parameters i.e., a pair of center coordinates, scaling in the horizontal and vertical directions, and the rotation angle. The segmentation of the region of interest in ultrasound images is done by minimizing the local energy function using gradient descent technique. Further optimization is carried out using Green’s theorem. Automatic localization poses an equal importance as segmentation and is achieved using sum of absolute difference method. The result of experimental validation has been done on the Signal Processing Lab, Brno University’s database of transverse and longitudinal B-mode ultrasound images consisting of 971 and 84 images, respectively. We attained accurate segmentation of the lumen boundary from transverse and longitudinal B-mode ultrasound images with an accuracy of 99.68% and 96.98% and Dice index of 93.33% and 91.70%, respectively. In addition, we attained an accuracy of 99.29% with Dice index of 91.78% for the segmentation of media adventitia boundary from transverse B-mode ultrasound images, which is the highest among the previously proposed methods.
Unsupervised Membership Inference Attacks Against Machine Learning Models

As a form of privacy leakage for machine learning (ML), membership inference (MI) attacks aim to infer whether given data samples have been used to train a target ML model. Existing state-of-the-art MI attacks in black-box settings adopt a so-called shadow model to perform transfer attacks. Such attacks achieve high inference accuracy but have many adversarial assumptions, such as having a dataset from the same distribution as the target model’s training data and knowledge of the target model structure. We propose a novel MI attack, called UMIA, which probes the target model in an unsupervised way without any shadow model. We relax all the adversarial assumptions above, demonstrating that MI attacks are applicable without any knowledge about the target model and its training set. We empirically show that, with far fewer adversarial assumptions and computational resources, UMIA can perform on bar with the state-of-the-art supervised MI attack.
Effect of Chloroform Application on Roughness and Wettability of the Root Canal Walls in Endodontic Retreatment

Statement of the Problem: The success of root canal therapy depends on root canal irrigation, disinfection, and sealing of root canal. Wettability and roughness of root dentine surface are important factors in root canal disinfection and sealing. Purpose: This study aimed to assess the effect of chloroform application on roughness and wettability of the root canal walls in endodontic retreatment. Materials and Method: This in vitro experimental study evaluated 70 sound extracted human anterior teeth. The specimens were then randomly assigned to 7 groups as follows: Chloroform (group 1), 1g gutta percha+chloroform (group 2), 2g gutta percha+ chloroform (group 3), 1g gutta percha+ 1g sealer+ chloroform (group 4), 2g gutta perch+ 2g sealer+chloroform (group 5), 1g sealer + chloroform (group 6) and 2g sealer + chloroform (group 7). One drop of distilled water was placed on each tooth to measure the contact angle and wettability. Photographs were obtained of an area measuring 50×50 µm2 in three directions under an atomic force microscope to measure the roughness. The tooth blocks were exposed to the abovementioned mixtures for 10 min, and then rinsed with saline. The roughness and wettability of each sample were measured before and after treatment. Data was analyzed using one-way ANOVA and Tukey’s test. Results: The roughness of all groups significantly decreased following treatment, except for groups 1 and 4. The contact angle increased in all groups after treatment (except for the chloroform group), which indicated decreased wettability. The roughness and the contact angle have shown no correlation. Conclusion: Application of chloroform for removal of gutta-percha and sealer in endodontic retreatment decreases the roughness and wettability of dentine.
Minimally Invasive Techniques for Kidney Transplantation: A Systematic Review

Introduction: With the advancement in laparoscopic and robotic surgery, there is a push towards minimally invasive surgery. For kidney transplantation, minimally invasive techniques have been explored with intention to minimize the incision and thus to reduce the surgical trauma and associated pain or wound complications, improving recovery and cosmetic appearance. The aim of this review is to provide an update on the development of minimally invasive technique for kidney transplantation. Methods: An electronic search of PubMed, Embase and Cochrane library database was conducted to identify the publications on surgical technique innovation for kidney transplantation by minimally invasive surgical technique between January, 1980 and September, 2016. Results: There were 5 papers and abstracts reported kidney transplant by using a smaller incision from 5 to 9 cm in selected 142 patients. There were 6 papers and abstracts described laparoscopic kidney transplant in 89 recipients in total, whereas there were 10 papers and abstracts demonstrated the safety and feasibility of robotic kidney transplantation in 300 recipients. One group has in particular applied robotic surgery to the obese recipients for kidney transplantation. Conclusion: Surgical technique innovation of minimally invasive technique for kidney transplantation is still at its early stage. The preclinical studies were conducted on the animals or human cadavers prior to application to the clinical human kidney transplantation. The technique challenge remains to minimize warm ischemic injury by improving proficiency of the vascular anastomosis under time pressure. The technique refinement is still needed to establish a better approach for kidney transplantation by minimally invasive technique. The terms “minimal incision + kidney transplantation”, “Minimally invasive + kidney/renal transplantation”; “smaller incision + kidney/renal transplantation”; “laparoscopic kidney/renal transplant” and “robotic kidney/renal transplantation” were used. Cross-referencing was also conducted to find further publications on minimally invasive approach for kidney transplantation. English language reports were selected and reviewed.
TRANSCRIPTOMIC CHARACTERIZATION AND ANALYSIS OF KEY BIOLOGICAL PATHWAYS ASSOCIATED WITH APHID RESISTANCE IN SORGHUM SORGHUM

Aphid damage is one of the most critical biotic stresses limiting sorghum production, worldwide. In this study, two sterile sorghum lines having aphid-resistant (APT) and aphid-sensitive (APS) phenotypes, along with eight hybrid lines were used to study the infestation and natural attack rates of aphids in three ecological zones. The results show that sorghum has a dominant genetic effect on aphid resistance, with aphid incidence ranging from 93.2% to 96.6% in the F 1 generation of crosses mated to APT sorghum sterile lines. APT vs APS transcriptome analysis suggested the ATP sorghum genotype may be able to stimulate defenses against aphid infestation, experienced less change in sugar and chlorophyll content than the APS genotype. The APT genotype also exhibited improved in vivo carbohydrate binding and endopeptidase inhibitor activity, which are two key biological metabolic pathways which are involved in inhibiting aphid feeding and growth, by converting glucose in organs to pyruvate in the cytoplasm via the glycolysis metabolic pathway, thereby reducing glucose content in tissues and creating an inhospitable environment for aphid growth.
An Attempt to Realize Uniﬁed Memory Extending GPGPU-Sim

—The current GPGPU-Sim is fully functional with CUDA 4.0. It is a complete functional and timing simulator publicly available. During the course of this project, we came across multiple simulators, extending GPGPU-Sim, which demand to achieve one or the other theoretical concepts. From our detailed investigation, we realized that all of them miss either functional or timing simulation aspect of a simulator. Thus, we felt the need of extending GPGPU-Sim to realize Uniﬁed Memory both functionally and from timing simulation perspective.
Personal exposimeter for radio frequency exposure assessment in the 60-GHz band

For the first time a personal Exposimeter (PE) is presented for radiation assessment in the 60-GHz band. Numerical simulations are used to design the PE and its uncertainty is assessed using on-body calibration measurements at 61 GHz. The PE consisting of three nodes (antennas) with vertical-horizontal-horizontal (VHH) polarization has a 50% prediction interval of 1.3 dB which is 3.1 dB lower than a single node experiment. The proposed PE has a 19.7 dB smaller uncertainty compared to the currently available exposimeters at lower frequencies. A 95 % confidence interval of 6.6 dB is measured on the response of the proposed PE.
du plan d'occlusion sur la dérive mésiale des arcades

As a rule, the occlusal plane in man is not flat but curved in the three dimensions. This cur- ved organization is related to a specifie phenomena : the continuity of the dental arch without diastema. The Page's proposai ofthe tangent law explains the sagittal organization ofthe mandibular teeth by geo- metrical analyses. A cephalometric analysis of 485 subjects, in natural dentition, is the basis for the present statistical study of the mandibular teeth sagittal inclination, related to the direction of the tangent. Mandibular incisors follow the tangent law, but the long axis of the posterior mandibular teeth exhibits a postero-anterior and progressive differential angle with the direction of the tangent : 15°, 20°, 25°, 28°. The differential angle with the direction of vertical strength during closure movement generâtes an horizontal strength component, with a tendency to create a forward tooth movement. This horizontal component of force is tightening the proximal contacts, maintaining the continuity of the dental arch : it also originates the mesial «drift» and mandibular incisor crowding. MOTS CLES - Plan d'occlusion / Courbe de Spee / Derive mesiale / Axe dentaire.
Streaming Approach to In Situ Selection of Key Time Steps for Time‐Varying Volume Data

Key time steps selection, i.e., selecting a subset of most representative time steps, is essential for effective and efficient scientific visualization of large time‐varying volume data. In particular, as computer simulations continue to grow in size and complexity, they often generate output that exceeds both the available storage capacity and bandwidth for transferring results to storage, making it indispensable to save only a subset of time steps. At the same time, this subset must be chosen so that it is highly representative, to facilitate post‐processing and reconstruction with high fidelity. The key time steps selection problem is especially challenging in the in situ setting, where we can only process data in one pass in an online streaming fashion, using a small amount of main memory and fast computation. In this paper, we formulate the problem as that of optimal piece‐wise linear interpolation. We first apply a method from numerical linear algebra to compute linear interpolation solutions and their errors in an online streaming fashion. Using that method as a building block, we can obtain a global optimal solution for the piece‐wise linear interpolation problem via a standard dynamic programming (DP) algorithm. However, this approach needs to process the time steps in multiple passes and is too slow for the in situ setting. To address this issue, we introduce a novel approximation algorithm, which processes time steps in one pass in an online streaming fashion, with very efficient computing time and main memory space both in theory and in practice. The algorithm is suitable for the in situ setting. Moreover, we prove that our algorithm, which is based on a greedy update rule, has strong theoretical guarantees on the approximation quality and the number of time steps stored. To the best of our knowledge, this is the first algorithm suitable for in situ key time steps selection with such theoretical guarantees, and is the main contribution of this paper. Experiments demonstrate the efficacy of our new techniques.
Impacts of good practice policies on regional and global greenhouse gas emissions

The report looks at the impact of "good practice"emission reduction policies in nine different areas globally and across six countries: China, Brazil, India, the US, Russia and Japan. These include renewable energy, a variety of energy efficiency standards (buildings, car fuel efficiecy, appliances and lighting, industry), hydrofluorocarbons (HFC.s), emissions from fossil fuel production, electric cars and forestry. The authors looked at the most ambitious "good practice" policies around the world that are being implemented now, and calculated the difference these would make if everybody were to apply them. If all governments follow those governments that currently adopt the best climate policies in just nin different areas, they could reduce emissions close to the levels needed to stay on track to hold global warming below 2 degrees C. The implementation of good practice policies is projected to stabilise greenhouse gas emissions at 49-50 GtCO2e by 2020, and decrease to 44- 47 GtCO2e by 2030- close to the 2 degrees C emissions range (30-44 GtCO2e) by 2030. Direct replication of good practice policies is projected to halt emissions growth in most regions sinificantly before 2030. In contrast, current policies are expected to see emissions to increase to around 54 GtCO2e by 2020 and 59-60 GtCO2e by 2030.
The Case for Using Guix to Enable Reproducible RISC-V Software & Hardware

Reproducible research is a serious challenge in the eld of computer architecture. RISC-V can potentially help improve reproducibility through the use of a standard, open instruction-set architecture along with open-source RISC-V software stacks and open-source RISC-V hardwaremodels. But the diversity of the RISC-V ecosystem can raise new issues complicating reproducible computer architecture research. In this paper, we present our on-going work to use the Guix package management system to help enable reproducible RISC-V software and hardware. We describe our recent work on porting RISC-V software stacks to Guix including bootstrapping through GNU Mes and integrating modern C++ cross compilers with RISC-V support. We also describe our recent work packaging RISC-V hardware models in Guix including the Spike functionallevel model, gem5 cycle-level model, and Ariane RTL model. Finally, we present a case study that illustrates a simple, reproducible experiment to cross-compile a Smith-Waterman sequence alignment workload for RISC-V and then run this workload on Spike, gem5, and Ariane.
Comparison of two Intranasal Sedatives, Midazolam versus Dexmedetomidine, in Children with High Dental Fear: a Randomized Clinical Trial

Statement of the Problem: Pharmacologic management of uncooperative behavior is a growing trend in dentistry. Determining the most appropriate drug, route of administration, and proper candidate for sedation have been the goal of several investigations. Purpose: The aim of this study was to compare the sedative effect of intranasal (IN) sedation of midazolam (MDZ) in compare to dexmedetomidine (DEX) while taking into consideration the effect of dental fear, and psychological status on sedation success. Materials and Method: This double-blind randomized clinical trial included 92 uncooperative dental patients aged 4-6. Study participants were randomly assigned to receive either 0.2mg/kg IN MDZ or 1µg/kg DEX. Sedation was evaluated using the Houpt sedation rating scale. Vital signs were recorded before and during sedation. Prior to sedation, the level of dental fear was determined through children's fear survey schedule-dental subscale (CFSS-DS). Psychological characteristics were screened using the strengths and difficulties questionnaire (SDQ). Data were analyzed using T-test, Mann-Whitney, Chi-square, and repeated-measures analysis of variance (ANOVA). Results: Overall ratings of sedation and subscales of sleep, crying, and movement were comparable between groups (p> 0.05); however, more acceptable behavior (overall scores (4+5+6) was observed in MDZ group compared to DEX group (64% vs. 47.7%) (p= 0.007). All participants were found to have abnormal levels of dental fear (CFSS-DS≥38). However, according to SDQ, the study participants have mainly shown normal behavioral status. A significant association was found between dental fear and sedation success (MDZ, p= 0.001, DEX, p= 0.03), while similar findings were not observed for psychological characteristics (MDZ, p= 0.09 and p= 0.41; DEX, p= 0.71 and p= 0.53). Physiological parameters remained within normal limits in both groups. Conclusion: Sedation with IN MDZ resulted in overall behaviors, which were more satisfactory in highly fearful pediatric dental patients. Despite baseline uncooperative behaviors, the psychological status of study participants were close to average and were not associated with sedation failure.
Node Graph Optimization Using Differentiable Proxies

Graph-based procedural materials are ubiquitous in content production industries. Procedural models allow the creation of photo-realistic materials with parametric control for flexible editing of appearance. However, designing a specific material is a time-consuming process in terms of building a model and fine-tuning parameters. Previous work [Hu et al. 2022; Shi et al. 2020] introduced material graph optimization frameworks for matching target material samples. However, these previous methods were limited to optimizing differentiable functions in the graphs. In this paper, we propose a fully differentiable framework which enables end-to-end gradient-based optimization of material graphs, even if some functions of the graph are non-differentiable. We leverage the Differentiable Proxy, a differentiable approximator of a non-differentiable black-box function. We use our framework to match structure and appearance of an output material to a target material, through a multi-stage differentiable optimization. Differentiable Proxies offer a more general optimization solution to material appearance matching than previous work.
The role of production expectations in visual world paradigm linking hypotheses

While widely used in psycholinguistics, the linking hypothesis for eye movements in the visual world paradigm is still poorly understood. Recent work on linking hypotheses for referential tasks in particular has found mixed support for the Referential Belief Link : that the proportion of looks to a referent in a time window reflects participants’ degree of belief that the referent is the intended target in that time window. Here we test the hypothesis that participants’ expectations for the utterances observed in an experiment modulate the extent to which the Referential Belief Link holds. This hypothesis is motivated by a simple idea: when utterances are unexpected, listeners engage in additional reasoning to make sense of the observed signal. In a re-analysis of a previous eye movement and in- cremental decision task dataset, in conjunction with two novel production experiments, we find that the more surprising an observed utterance is, the smaller the correlation between explicit and implicit beliefs is. We discuss the importance of par- ticipants’ production expectations in research using the visual world paradigm.
Attribute Prediction in the Zero-Shot Setting as Multiple Instance Learning

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reﬂect the content of an image is not always straightforward, as per-image ground truth attributes are often not available. We propose applying the Multiple Instance Learning (MIL) paradigm to attribute learning (AMIL) while only using class-level labels. We allow the model to under-predict the positive attributes, which may be missing in a particular image due to occlusions or unfavorable pose, but not to over-predict the negative ones, which are almost certainly not present. We evaluate it in the zero-shot learning (ZSL) setting, where training and test classes are disjoint, and show that this also allows to proﬁt from knowledge about the semantic relatedness of attributes. In addition, we apply the MIL assumption to ZSL classiﬁcation and propose MIL-DAP, an attribute-based zero-shot classiﬁcation method, based on Direct Attribute Prediction (DAP), to evaluate attribute prediction methods when no image-level data is available for evaluation. Experiments on CUB-200-2011, SUN Attributes and AwA2 show improvements on attribute detection, attribute-based zero-shot classiﬁcation and weakly supervised part localization.
Screening plants for medicines against Klebsiella & Pseudomonas species infections

Klebsiella & Pseudomonas species are multi drug resistant bacteria. These bacteria are resistant to number of antimicrobial agents. The research work was aimed at killing and inhibiting the growth of these multi drug resistant pathogens, by using phytochemicals. The phytochemicals are secondary metabolites produced by plants. According to WHO medicinal plants are best products for maintaining human health. Plants like Terminalia bellerica (Behada) and Santalum album (Chndan) found to be the most effective against all isolated multi drug resistant Pseudomonas species and Klebsiella species. 20 pathogens were isolated on MacConkeys agar plate. Out of these isolates, all isolates showed resistance to the more than two antibiotics. All of them studied for colony morphology, cell morphology, biochemical nature & 16srRNA sequencing. The 10 isolated multi drug resistant Klebsiella species were named as K1 to K10. The 10 isolated multi drug resistant Pseudomonas species were named as P1 to P10.