Testing Interestingness Measures in Practice: A Large-Scale Analysis of Buying Patterns

Understanding customer buying patterns is of great interest to the retail industry and has shown to benefit a wide variety of goals ranging from managing stocks to implementing loyalty programs. Association rule mining is a common technique for extracting correlations such as "people in the South of France buy ros\'e wine" or "customers who buy pat\'e also buy salted butter and sour bread." Unfortunately, sifting through a high number of buying patterns is not useful in practice, because of the predominance of popular products in the top rules. As a result, a number of "interestingness" measures (over 30) have been proposed to rank rules. However, there is no agreement on which measures are more appropriate for retail data. Moreover, since pattern mining algorithms output thousands of association rules for each product, the ability for an analyst to rely on ranking measures to identify the most interesting ones is crucial. In this paper, we develop CAPA (Comparative Analysis of PAtterns), a framework that provides analysts with the ability to compare the outcome of interestingness measures applied to buying patterns in the retail industry. We report on how we used CAPA to compare 34 measures applied to over 1,800 stores of Intermarch\'e, one of the largest food retailers in France

Maximizing Connection Density in NB-IoT Networks with NOMA

International audienceWe address the issue of maximizing the number of connected devices in a Narrowband Internet of Things (NB-IoT) network using non-orthogonal multiple access (NOMA). The scheduling assignment is done on a per-transmit time interval (TTI) basis and focuses on efficient device clustering. We formulate the problem as a combinatorial optimization problem and solve it under interference, rate and sub-carrier availability constraints. We first present the bottom-up power filling algorithm (BU), which solves the problem given that each device can only be allocated contiguous sub-carriers. Then, we propose the item clustering heuristic (IC) which tackles the more general problem of non-contiguous allocation. The novelty of our optimization framework is twofold. First, it allows any number of devices to be multiplexed per sub-carrier, which is based on the successive interference cancellation (SIC) capabilities of the network. Secondly, whereas most existing works only consider contiguous sub-carrier allocation, we also study the performance of allocating non-contiguous sub-carriers to each device. We show through extensive simulations that non-contiguous allocation through IC scheme can outperform BU and other existing contiguous allocation methods

Dentofacial and Cranial Changes in Down Syndrome

AbstractObjectivesThis study aimed to determine the prevalence of certain oral characteristics usually associated with Down syndrome and to determine the oral health status of these patients.MethodsThe cross-sectional study was conducted among patients attending a special education program at Faculty of Dentistry, Jamia Millia Islamia, Delhi, India. The study design consisted of closed-ended questions on demographic characteristics (age, sex, and education and income of parents), dietary habits, and oral hygiene habits. Clinical examination included assessment of oral hygiene according to Simplified Oral Hygiene Index (OHI-S), dental caries according to decayed, missing, and filled teeth (DMFT) index, periodontal status according to the Community Periodontal Index of Treatment Needs (CPITN), and malocclusion according to Angles classification of malocclusion. Examinations were carried out using a using a CPI probe and a mouth mirror in accordance with World Health Organization criteria and methods. Craniometric measurements, including maximum head length and head breadth were measured for each participant using Martin spreading calipers centered on standard anthropological methods.ResultsThe majority of the patients were males (n = 63; 82%) with age ranging from 6–40 years. The Intelligence Quotient (IQ) score of the patients indicated that 31% had moderate mental disability and 52% had mild mental disability. 22% exhibited hearing and speech problems.12% had missing teeth and 15% had retained deciduous teeth in adult population. The overall prevalence of dental caries in the study population was 78%. DMFT, CPITN and OHI scores of the study group were 3.8 ± 2.52, 2.10 ± 1.14 and 1.92 ± 0.63 respectively. The vast majority of patients required treatment (90%), primarily of scaling, root planing, and oral hygiene education. 16% of patients reported CPITN scores of 4 (deep pockets) requiring complex periodontal care. The prevalence of malocclusion was 97% predominantly of Class III malocclusions. Further 14% presented with fractured anterior teeth primarily central incisor. The percentage means of cephalic index was 84.6% in the study population. The brachycephalic and hyperbrachycephalic type of head shape was dominant in the Down syndrome individuals (90%).ConclusionThe most common dentofacial anomaly seen in these individuals was fissured tongue followed by macroglossia

Analysis of Downlink Connectivity in NB-IoT Networks Employing NOMA with Imperfect SIC

International audienceWe study the problem of maximizing the number of served devices in a non-orthogonal multiple access (NOMA) based Narrowband Internet of Things (NB-IoT) network for supporting massive connectivity in the downlink. We analyze this problem under practical system limitations of imperfect successive interference cancellation (SIC) at the receiver along with data rate, power and bandwidth constraints. We propose a strategy for joint device and power allocation through an iterative solution for a system of linear equations on each sub-carrier that maximizes the number of connected devices. We evaluate the performance of the proposed solution over a wide range of service scenarios through extensive computer simulations and demonstrate the sensitivity of connectivity in power domain NOMA based NB-IoT systems to the residual interference resulting from imperfect SIC

Downlink Connection Density Maximization for NB-IoT Networks using NOMA with Perfect and Partial CSI

International audienceWe address the issue of maximizing the number of connected devices in a Narrowband Internet of Things (NB-IoT) network using non-orthogonal multiple access (NOMA) in the downlink. We first propose an optimal joint sub-carrier and power allocation strategy assuming perfect channel state information (CSI) called Stratified Device Allocation (SDA), that maximizes the connectivity under data rate, power and bandwidth constraints. Then, we generalize the connectivity maximization problem to the case of partial CSI, where only the distancedependent path-loss component of the channel gain is available at the base station (BS). We introduce a novel framework called the Stochastic Connectivity Optimization (SCO) framework. In this framework, we propose a heuristic improvement to SDA namely SDA with Excess Power (SDA-EP) algorithm for operation under partial CSI. Furthermore, we derive a concave approximation (SCO-CA) algorithm of near-optimal performance to SCO given the same amount of CSI. Through computer simulations, we show that SDA-EP and SCO-CA outperform conventional NOMA and OMA schemes in the presence of partial CSI over a wide range of service scenarios

State-of-the-art in string similarity search and join

String similarity search and its variants are fundamental problems with many applications in areas such as data integration, data quality, computational linguistics, or bioinformatics. A plethora of methods have been developed over the last decades. Obtaining an overview of the state-of-the-art in this field is difficult, as results are published in various domains without much cross-talk, papers use different data sets and often study subtle variations of the core problems, and the sheer number of proposed methods exceeds the capacity of a single research group. In this paper, we report on the results of the probably largest benchmark ever performed in this field. To overcome the resource bottleneck, we organized the benchmark as an international competition, a workshop at EDBT/ICDT 2013. Various teams from different fields and from all over the world developed or tuned programs for two crisply defined problems. All algorithms were evaluated by an external group on two machines. Altogether, we compared 14 different programs on two string matching problems (k-approximate search and k-approximate join) using data sets of increasing sizes and with different characteristics from two different domains. We compare programs primarily by wall clock time, but also provide results on memory usage, indexing time, batch query effects and scalability in terms of CPU cores. Results were averaged over several runs and confirmed on a second, different hardware platform. A particularly interesting observation is that disciplines can and should learn more from each other, with the three best teams rooting in computational linguistics, databases, and bioinformatics, respectively

Investigating Flavonoid Extracts from Medicinal Plants: Evaluating their Anti-Cancer Potential, Mechanisms, and Synergistic Impact on Colon Cancer

Colon cancer, the leading cause of global cancer-related mortality, demands innovative therapeutic approaches to combat its formidable impact. This empirical study embarks on a quest to unlock novel avenues for colon cancer treatment by investigating the anti-cancer potential of flavonoid extracts sourced from medicinal plants. Our research journey commences with an in-depth examination of the staggering global burden imposed by colon cancer and the inherent limitations of current therapeutic regimens. In response to this pressing challenge, we spotlight the emerging enthusiasm for natural compounds, specifically flavonoids, as transformative agents within the realm of cancer research and therapy. In our pursuit of innovative solutions, we meticulously select medicinal plants celebrated for their flavonoid-rich content and extract these bioactive compounds with precision. Rigorous phytochemical analyses unveil the specific flavonoids at play. In a series of in vitro experiments employing colon cancer cell lines, we uncover a compelling narrative of concentration-dependent cytotoxicity, underscoring the remarkable anti-proliferative attributes of these extracts. Moreover, our investigations reveal that flavonoid extracts possess the remarkable capability to induce apoptosis, substantiated through Annexin V/PI staining and caspase activation assays. As we delve deeper into mechanistic insights, a rich tapestry unfolds, elucidating the intricate modulation of pivotal apoptosis-related pathways by these natural compounds. This study not only furnishes compelling evidence of flavonoid extracts' anti-cancer potential against colon cancer but also underscores the pivotal role of natural compounds in the ever-evolving landscape of cancer research, offering a beacon of hope for pioneering therapeutic strategies. The journey has only begun, and further investigations, alongside rigorous clinical trials, are warranted to harness the full therapeutic potential of flavonoid-based interventions in colon cancer management, potentially redefining the paradigm of cancer treatment

Food Quality-Dependent Modulation Of Caenorhabditis Elegans Reproductive Physiology

Reproductive disorders and infertility affect close to 80 million people worldwide with no immediate cure in sight. Multiple studies have implicated environmental factors, such as temperature, photoperiodism, and toxic environmental contaminants, which alter our reproductive capabilities. However, the mechanisms through which our surroundings influence our reproduction remain unclear. The molecular dissection of these reproductive mechanisms is exceptionally challenging to conduct in humans. However, with its cell biology and genetic tool kits, the worm C. elegans provides a more tractable model to study the effects of the environment on reproduction. I have focused on how food quality influences different aspects of C. elegans reproductive physiology, which shares many similarities with that of humans. For the worm, its bacterial food source is also a major source of its environmental cues. Because the sensory system acts at the interface of the environment and animal physiology, I have hypothesized that the sensory system will play an important role in many aspects of reproduction, including germline development and physiology. The study of the sensory influence on the germline could yield novel therapies against reproductive diseases and infertility. For my thesis, I have identified specific sensory neurons that modulate distinct stages of C. elegans oocyte development in response to food quality. The taste neuron ASJ promotes early oogenesis onset on certain food sources, like E. coli CS180, by expressing a specific insulin-like peptide (ILP) known as INS-6. In contrast, the olfactory neuron AWA promotes faster oocyte maturation on these same food sources, but in an insulin-independent manner. Since I have also shown that oocyte maturation depends on the synthesis of the monounsaturated fatty acid (MUFA) palmitoleic acid, it is possible that the AWA-dependent effect on oocyte maturation involves this MUFA activity. Although insulin signaling does not mediate the AWA effect, insulin signaling does play two roles in oocyte maturation: one that is food type-dependent during the early phases and another that is food type-independent at the later phases. The early phases of oocyte maturation require the intestinal expression of the ILP INS-1, whereas the later phases entail other ILPs. Thus, discrete aspects of C. elegans oogenesis depend on distinct sensory cues that are potentially encoded and integrated by specific ILP and non-ILP signals. I have also shown that food quality influences other features of C. elegans reproduction, such as germline proliferation, spermatogenesis and egg laying. The food source E. coli CS180 inhibits germline proliferation, but promotes faster spermatogenesis, like oogenesis. This suggests that this particular food source favors germ cell differentiation over germ cell proliferation. Future work will address (i) the nature of the CS180-derived cues that promote germ cell differentiation and (ii) whether the same or different sensory neurons or ILPs also influence these other aspects of C. elegans physiology. Together, my thesis work shows that successful reproduction depends on different sensory neurons and non-neuronal tissues that sense and integrate complex environmental cues through the activities of distinct signaling mechanisms

Maternal body size and age govern reproduction and offspring phenotype in the zig-zag ladybird beetle (Menochilus sexmaculatus)

Maternal effects are possible channels through which mothers provision their offspring differentially, thereby affecting offspring phenotype. We investigated maternal effects in the zig-zag ladybird beetle (Menochilus sexmaculatus (Fabricius, 1781) = Cheilomenes sexmaculata (Fabricius, 1781)) in response to body size (induced by different feeding regimes during larval development) and their age within the reproductive cycle. Different-sized females were permitted to mate and were provided with daily-replenished ad libitum prey. After mating, reproductive output and developmental duration of offspring from different oviposition days were recorded. We hypothesized that small females would lay smaller and fewer eggs than larger females, and that egg mass would also reduce with increased maternal age. In our study, the larger mothers laid more eggs per day. Small and large mothers oviposited maximally at middle age. Maternal age did not influence the egg mass, although it was slightly higher in the case of older, larger females. Offspring from old, small and large mothers developed rapidly. This nimble development could be an adaptive strategy for the use of ephemeral aphid patches. The results of the study are indicative of this ladybird species’ ability to adjust their offspring’s life-history traits, a feature more prominent in larger females.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Numerical Analysis of Atherosclerosis and Aneurysm in Carotid Bifurcations using Computational Fluid Dynamics

Atherosclerosis and Aneurysm are some of the conditions in patients suffering from vascular diseases. These vascular defects can cause severe damage to cardiovascular system (CVS), if not properly diagnosed. The advent of advanced numerical and computational techniques has enabled the researchers to accurately design and simulate the flow of blood through the complex flow systems. Current state of published research is mostly based on simplified modelling tools and qualitative analysis that is limited to macro level description of the flow field. There is a need to diagnose the flow structure at micro level in order to carry out hemodynamic analysis of such defects. Several cardiovascular models of a bifurcation in the carotid artery have been generated using Computational Fluid Dynamics based techniques in the present investigation. These models represent healthy and defective carotid bifurcations, where the defective bifurcations represent atherosclerotic and aneurysm conditions. It has been observed that the defects in the carotid bifurcation affect local Wall Shear Stress WSS) significantly. The magnitude of wall shear stress has been shown to be crucial in ulceration and plaque formation