Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analysis of Post-Election Audit Data for the November 8, 2022 State Election

This report presents an analysis of the returns from the post-election audit performed in the State of Connecticut following the November 8, 2022 state election. The audit involved a random selection of 5% of the precincts in which ballots were cast. In each precinct so selected, the ballots cast on election day were either hand-counted or counted with electronic assistance.1 A total of 36 precinct audits were submitted for analysis, comprising 512 audit records. Precincts in two towns selected for audit, Greenwich and Waterbury, were later exempted as a result of a town-wide recount. The specific goal of the analysis was to use statistical methods to detect instances of tabulator malfunction. The 512 precinct audit results evaluated show discrepancies between tabulated and audited totals that are consistent with anticipated human error in counting or ballot handling. The analysis revealed no conclusive signs of tabulator malfunction.
Tracking, But Make It Offline: The Privacy Implications of Scanning QR Codes Found in the World

—QR Codes have become a pervasive mechanism for encoding machine-readable digital data in the offline world. As the Internet age has taught us, mechanisms that become pervasive very often engender privacy concerns regarding their use. As such, here we conduct an investigation of the privacy implications of the QR Code ecosystem as it exists today. We find that there are several shortener services with substantial popularity, and investigate the extent to which these shortener services conduct various types of tracking of individuals who interact with the created QR Codes. Additionally, we collect 948 QR codes posted within the world, and evaluate them for various types of tracking as well. Overall, we find no evidence that QR codes are a substantial or unique privacy threat when compared to other link sharing mechanisms available online. Even so, the theoretical potential for surreptitious tracking exists, and more in depth study of the QR Code ecosystem will allow for deeper investigation of the relationship between online and offline tracking.
SASPAR: Shared Adaptive Stream Partitioning

Data partitioning induces network transfers and dominates the cost of stream data analytics. Moreover, partitioning streaming data for multiple stream queries in the same cluster can easily saturate the network bandwidth and lead to high end-to-end latencies.The goal of this paper is to share the partition operation in streaming workloads and maximize the sharing opportunities for multiple stream queries. However, there are several challenges, such as minimizing data copy, optimizing the partitioning strategy for multiple queries, and minimizing latency.We propose SASPAR, Shared Adaptive Stream Partitioner, which is able to share data partitioning among multiple stream queries. Our contributions are threefold. First, we propose a new technique to optimize the partitioning strategy for multiple stream queries. Second, we present an adaptive query execution framework that performs optimizations at run-time, without stopping the query execution plan. Third, we utilize meta-heuristics and machine learning when solving the underlying optimization problem takes more time than expected.SASPAR is designed as a versatile layer to sit on top of a stream processing engine (SPE). We operate SASPAR on top of three state-of-the-art SPEs with hundreds of stream queries. Our experimental results show that SASPAR improves the performance (throughput and latency) of all underlying SPEs by up to 3x.
A Framework for Proactive and Adaptive Natural Language Interaction in Dynamic and Unstructured Environments

—Humans should be able to collaborate with robots without sacriﬁcing their own operational tempo, and consequently the communication should be efﬁcient and un-inhibitive. Physically-grounded language interfaces provide a generally-accessible solution that allows the human to communicate with their robot teammates. However, both robot perception and grounded language understanding are computationally expensive in unstructured, dynamic environments and thus impose an efﬁciency bottleneck for collaboration. One recent approach attempts to address this problem by reactively building compact, task relevant world models by exploiting the information in the received utterance. Another recent approach exploits the idle time before receiving an utterance to proactively generate and ground the likely phrases. In this work, we propose an integrated framework that leverages both of these seemingly contradictory models in order to maximize the runtime performance of language understanding.
HELMET, TRIPLE RIDE AND VEHICLE NUMBER PLATE DETECTION

- The 3-way helmet and registration code recognition machine is one such shrewd transportation gadget. The goal is to extract the numbers from the plate. This method is utilized in various security applications for registration code and helmet retrieval. This painting is based totally on facet detection and green morphological operations. Character segmentation is the technique of extracting characters and numbers from a registration code. Voices within the picture are removed by using filtering strategies. Character recognition uses Optical Character Recognition (OCR) technology. In OCR, a character filters out is matched against a pattern the use of a matching algorithm, and the individual is ultimately extracted. Motorcycle accidents have been growing hastily over the years in many countries. A helmet is the primary protecting gadget of motorcyclists. But many drivers do not use it. The cause of a helmet is to shield the driving force's head in case of a twist of fate
Is habitat suitability sex-specific? A study of the Indian Giant Squirrel ( Ratufa indica maxima ) in the Western Ghats of India

Habitat suitability difference between sexes results in sex-specific dispersal. Although this behaviour is one o f the key factors in understanding population dynamic s, there are limited studies to evaluate it in arboreal specie s. We studied the distribution of the Indian Giant Squir-rel (IGS; Ratufa indica maxima ) from a sex perspective. We also evaluated potentiallly suitable habitat types for t he species in the Nelliyampathy Reserve Forest, Western G hats, Kerala, India. We used the sweep survey metho d to record the distribution pattern of squirrels and analysed the influence of climatic layers and other variable s on the distribution using MaxEnt. The study revealed that there was a difference between the sexes in habitat selection. Males preferred more land-use types than females, which were restricted to only certain land-use types. Some of the major factors that determined the dis tribution of species were distance from urban settle-men t (50.1%), distance from shade plantation (23.2%), d istance from rocky outcrop (9.2%), minimum tempera-t ure of the coldest month (9%) and precipitation of the wettest quarter (8.5%). The final MaxEnt model output predicted 49.07% suitable habitat for IGS, of which 45.47% and 34.42% were suitable for males and females respectively, with an overlap of 30.82% between t he sexes. We suggest that it would be important to in-clud e a sex perspective in species habitat suitability studies in order to gain insights into sex-related habitat specificity and its role in dispersal.
Cost-Effective Analysis of Control Strategies to Reduce the Prevalence of Cutaneous Leishmaniasis, Based on a Mathematical Model

Leishmaniasis is a neglected tropical vector-borne epidemic disease, and its transmission is a complex process. Zoonotic transmission to humans or animals occurs through the bites of female Phlebotominae sand flies. Here, reservoir is considered as a major source of endemic pathogen pool for disease outbreak, and the role of more than one reservoir animal becomes indispensable. To study the role of the reservoir animals on disease dynamics, a mathematical model was constructed consisting of susceptible and infected populations of humans and two types of reservoir (animal) and vector populations, respectively. Our aim is to prevent the disease by applying a control theoretic approach, when more than one type of reservoir animal exists in the region. We use drugs like sodium stibogluconate and meglumine antimoniate to control the disease for humans and spray insecticide to control the sand fly population. Similarly, drugs are applied for infected reservoir animals of Types A and B. We calculated the cost-effectiveness of all possible combinations of the intervention and control policies. One of our findings is that the most cost-effective case for Leishmania control is the spray of insecticides for infected sand fly vector. Alternate strategic cases were compared to address the critical shortcomings of single strategic cases, and a range of control strategies were estimated for effective control and economical benefit of the overall control strategy. Our findings provide the most innovative techniques available for application to the successful eradication of cutaneous leishmaniasis in the future.
Why Do Mental Disorders Persist ? Evolutionary Foundations for Psychiatry

Discovering why natural selection has left humans vulnerable to mental disorders will make psychiatry more sensible and effective, but defining the appropriate objects and kinds of explanation remains challenging. Asking how a disorder increases fitness is a mistake; disorders are not adaptations and they do not have evolutionary explanations. The correct objects of explanation are the traits that make all members of a species vulnerable to a disorder. Task 1 is to describe the evolutionary origins and functions of the traits involved. Task 2 is to describe the proximate processes that result in the disorder. Task 3 is to discover why natural selection left the traits vulnerable to malfunction. Five main kinds of explanation need to be considered: stochasticity, path dependence, mismatch, trade-offs that benefit the individual and traits that benefit gene transmission at a cost to the individual. Depression, addiction, eating disorders, autism and schizophrenia are used to illustrate the opportunities and challenges of framing and testing hypotheses about vulnerability. Multiple explanations are often needed for a single disorder, frustrating the wish for simplicity. However, recognising the fundamental differences between organic and designed systems offers opportunities for resolving – or at least understanding – some enduring controversies
NANO-BIOFERTILIZERS FOR SUSTAINABLE AGRICULTURE

Conventional fertilizers play a key role in increasing global agricultural production. The world consumption of three major nutrients viz., nitrogen (N), phosphate (P) and potash (K) have increased consistently over the past years especially after green revolution. Over the period of time, application of chemical fertilizers above threshold limit leads to decreased soil fertility, lesser crop yield, emergence of pests and disease, loss of biodiversity and environmental pollution. Imbalanced application of chemical fertilizers also causes low nutrient use efficiency, high mineral leaching, low nutrient assimilation potency, depletion of organic matter content and deficiency of secondary and micronutrients in soil and plant. Too much dependence on chemical fertilizer like ammonia, urea, nitrate or phosphate compounds in agriculture leads to severe damage to both environmental ecosystem as well as animal and human health. This has made the environmentalists and agricultural scientists to search for a nontoxic eco-friendly alternative to achieve the desired goal, to increase the agriculture productivity without associated side problems. Biofertilizers have emerge out a promising tool and act as supplementary, renewable and eco-friendly source of plant nutrients. The global bio-fertilizer market was valued more than the USD1.49 billion in 2019, growing at a compound annual growth rate (CAGR) of around 12.8% from 2020-2027.Currently, nitrogen-fixing biofertilizers represent the biggest segment dominated the global biofertilizer market with a share of 71.2% in 2019 followed by phosphate fixing biofertilizers.Biofertilizer mainly constituted of live formulations of beneficial microorganism which when applied to seed, plant surface or soil, promote plant growth by increasing the supply of essential nutrients to the plants. The most commonly used biofertilizers are: NANO-BIOFERTILIZERS FOR SUSTAINABLE AGRICULTURE Dr. Ruchi Sood
Evaluating Roles of Two Na/H Antiporters in Staphylococcus aureus Nitric Oxide Resistance

Staphylococcus aureus, a Gram-positive pathogen, has been a pervasive public health issue in the form of community-acquired methicillin-resistant S. aureus (CA-MRSA; Diep et al. 2006; Klevens et al. 2007). Despite the human immune response having multiple mechanisms to combat pathogens, S. aureus has the unique ability to resist nitric oxide (NO·), a major immune component (Grosser et al. 2016; Grosser et al. 2018). This resistance has drawn much scientific interest toward developing drug targets. A Tn-Seq performed by Grosser et al. (2018) identified two genes that encoded for Na/H antiporters which impacted S. aureus during NO· stress. However, there has been no published scientific work evaluating their impact. Other research has established a compensatory relationship between specific S. aureus antiporters and pH and proton regulation during non-NO· stress (Vaish et al. 2019). Thus, it is highly likely that similar relationships exist for additional antiporters when CA-MRSA encounters high salt and acidity from the human immune response. The aims of this research are to develop single and double mutants of two genes, NhaC and USA300_0617 under a modified allelic exchange method (Fuller et al. 2011). After developing a wild-type variant (WT), we will measure growth curves and compare mutants to WT under NO·, low pH, anaerobiosis, and high salt stress. Given our evaluation of antiporters, membrane potential will also be reviewed. To obtain additional characterization data, mutants will be exposed a range of antibacterial compounds.
Thesis Booklet Optimized Tailoring of Agile Project Management Frameworks From Combining Scrum and PMI towards Multivariate Optimization for Project Process Relevance Factors

ed process steps were described to perform a multivariate regression and optimization approach generically based on the steps taken in Hypothesis 2. These were enriched with additional steps like ongoing optimization through feedback loops and automated data collection attempts. Six different subsets of data serve as the basis for case study applications for the optimization model resulting in 6 different distribution results. Although the process itself can be followed during this application, this part of the Hypothesis can only be partly confirmed since proposed process steps, like automated data collection, are not included in the case study and some of the optimization results show unsatisfying statistical parameters, resulting in low trustworthiness of the actual optimization values.
Traditional Medicine Combination Therapy Is A Promising Strategy for MRSA Infection

Methicillin-resistant Staphylococcus aureus (MRSA) is a superbug that often causes serious inflammation-related injuries. Host immune defense against MRSA infection and MRSA immune evasion strategies are the main mechanisms of these injuries. Conventional drugs, such as antibiotics, optimized antibiotics and vaccines, can treat MRSA infections, but their use is limited because of drug-resistance and impairment of immunity. Traditional medicine (TM) therapies, presently used to address these unmet clinical needs and treat injuries, are regarded as a potential solution to combat MRSA infection. This review systematically summarizes the immune mechanisms of MRSA infection, analyzes the efficacy characteristics and corresponding mechanisms of conventional and TM therapies in treating injuries, and discusses the potential advantages of combined therapy. Furthermore, several appropriate immune responses-related conditions that could be treated with the combination therapy were summarized, and new perspectives on the clinical and basic research on this combination therapy were proposed. This review lays a foundation for the development of anti-MRSA therapies and provides novel strategies and methods for the treatment of inflammation-related injuries caused by multiple drug-resistant bacteria.
Influence comparée d’une alimentation à base de graines de soja cuites ou grillées sur les performances des porcs en croissance finition

heat) of soybeans on the performances of grower-finisher pigs. Twenty hybrid male piglets, averaging 15.4 ± 0.8 kg initial body weights were allotted to four experimental diets (five replicates per treatment) based on soybean meal, cotton seed cake, cooked or roasted soybeans over a 98-day period. The rations containing the commonly used soybean meal and cotton seed cake were used as control diets. Results showed that the weight gain and feed conversion ratio obtained with diets containing roasted and cooked soybeans were significantly (P 0.05) compared to the soybean meal diet. Comparison of the two methods of heat treatment showed no significant difference on animal performances. Feed costs to produce one kilogram live weight, calculated as mean costs for both growth phases, although not significant between treatments, showed a slightly lower value in roasted soybean diets. These results show that the roasting method can be used with the same advantages as the cooking method.
Management Research and Practice

The main purpose of this research was to explore the moderating role of psychological well-being in the relationship between remote working and flow. Based on that, a survey was conducted on 238 managers and administrative staff who are working in the IT industry, Telecommunications industry, Retail industry and Banking sector in Istanbul, Turkey. Remote working scale developed by Grant has been used to measure e-working (17 statements). Flow scale developed by Bakker has been used to measure the flow, a scale consisting of 13 statements. The scale developed by Diener, Scollon & Lucas and adapted to Turkish version by Telef was used to measure the level of psychological well-being (8 items). According to the results of the analysis, there is a relationship between remote working and flow. Also, it was revealed that psychological well-being has a mediating role between remote working and flow. The value of this study consist in highlighting the related aspects concerning remote working and flow experience of Turkish employees working in the IT industry, Telecommunications industry, Retail industry and Banking sector and their psychological wellbeing levels.
Entropy and Graph Energy of Complex Networks

Abstract: The concept of graph energies has remained mostly a theoretical idea with no practical applications in the world of complex and social networks. Graph energy is the energy of the matrix representation of the graph, where matrix energy is the sum of absolute values of the eigenvalues of the matrix. Although theoretical properties of various graph energies have been investigated in the past, there has never been a serious attempt to utilize them in practice. In this work we investigate the usefulnes and usability of graph energies and their entropies in describing a wide spectrum of networks. We show that when graph energies are applied to local egocentric networks within larger topological structures, the values of these energies correlate strongly with several centrality indexes. In particular, for some network models, graph energies tend to correlate very strongly with the betweenness and the eigencentrality of nodes. As the computation of these centrality measures is expensive and requires global processing of a network, our research opens the possibility of devising efficient algorithms for the estimation of these centrality metrics based only on local information.
Accounting for the differential inter-system bias (DISB) of code observation in GPS+BDS positioning

Abstract If the associated differential inter-system biases (DISBs) are priori known, only one common reference satellite is sufficient, which is called the inter-system model. The inter-system model can help to maximize the redundancy of the positioning model, and thus can improve the positioning performance, especially in harsh environment. However, in practice use not all receivers can be calibrated with DISBs in advance. In this paper, taking combined GPS and BDS pseudorange positioning as the example, we compare three positioning models and their positioning performance. One is traditional intra-system model, and the other two belongs to the inter-system models, i. e. the model with calibration of DISB and the model with real-time estimation of DISB parameter. Positioning performance using the three models is evaluated with simulated obstructed environments. It will be shown that besides the model with calibration of DISB, the model with real-time estimation of DISB parameter can also effectively improve positioning accuracy and reliability compared with the traditional intra-system model, especially for the severely obstructed environment with only a few satellites observed. When no more than 7 satellites visible, the positioning accuracies in each directions can be improved by no less than 15 %. The proposed model can be used alternatively when no priori DISB calibration is available.
A Tale of Two Packing Problems: Improved Algorithms and Tighter Bounds for Online Bin Packing and the Geometric Knapsack Problem

Abstract In this thesis, we deal with two packing problems: the online bin packing and the geometric knapsack problem. In online bin packing, the aim is to pack a given number of items of dierent size into a minimal number of containers. The items need to be packed one by one without knowing future items. For online bin packing in one dimension, we present a new family of algorithms that constitutes the rst improvement over the previously best algorithm in almost 15 years. While the algorithmic ideas are intuitive, an elaborate analysis is required to prove its competitive ratio. We also give a lower bound for the competitive ratio of this family of algorithms. For online bin packing in higher dimensions, we discuss lower bounds for the competitive ratio and show that the ideas from the one-dimensional case cannot be easily transferred to obtain better two-dimensional algorithms. In the geometric knapsack problem, one aims to pack a maximum weight subset of given rectangles into one square container. For this problem, we consider oine approximation algorithms. For geometric knapsack with square items, we improve the running time of the best known PTAS and obtain an EPTAS . This shows that large running times caused by some standard techniques for geometric packing problems are not always necessary and can be improved. Finally, we show how to use resource augmentation to compute optimal solutions in EPTAS -time, thereby improving upon the known PTAS for this case.
An optical fiber Fabry–Pérot micro-pressure sensor based on beam-membrane structure

In this paper, an optical fiber Fabry–Pérot (FP) sensor for micro-pressure measurement is proposed. The FP interferometric cavity is composed of an end face of the incident optical fiber and a sensitive silicon diaphragm. The sensitive silicon diaphragm creatively utilizes a beam-membrane structure which is fabricated by micro-electro-mechanical system manufacturing technology. The finite element method simulation results show that the beam-membrane structure can achieve higher sensitivity and better linearity. The sensor performance test platform is built by a ASE-wide spectrum light source, optical spectrum analyzer, micro-pressure gas source and so on. The phase demodulation method is employed to demodulate the cavity length signal from the spectrum. The measure range of the sensor is 0–10 KPa, and the experimental sensitivity of the cavity length can reach to 242 nm KPa−1.