Undergraduate Research Journal, Volume 15

Table of Contents: The Effects of Snorkel-Based Tourism on the Behavior of Reef Fishes / by Savannah Clapp, Lauren Rowsey, and Jordan Grant (p.1-18) -- People Broken Into Pieces Trying to Join: Byzantine Erotica and the Provocative Paradox / by Kendall DeBoer (p.19-28) -- The Legacy of 1830 Land Cover on Present-Day Massachusetts Forest Composition / by Sofie McComb (p.29-58) -- The Role of Labels in Making Inferences about Group Categorization / by Subhashini Madhavan (p.59-76) -- Transcending Autobiography: Simultaneity and Meaning in Elisabet Ney’s Lady Macbeth / by Kendall DeBoer (p.77-92) -- Comparison of Microbial Diversity in Local Wasps and Plant Surfaces / by Dylan Fall and Jo-anne Holley (p.93-104) -- Ambiguity in Biotechnology Patent Policy: Lessons from Association for Molecular Pathology v. Myriad Genetics, Inc. / by Chari Noddings (p.105-126) -- About the uncountability of the number of irrational powers of irrational numbers evaluated as rationals and solutions’ estimation for xx=y and xx =y / by Anca Andrei (p.127-133)Senate of College Council

Limiting the Use of the RICO Act as a Defense to Hostile Corporate Takeovers

This Note argues that RICO could be a legitimate defense to a hostile corporate takeover pursuant to a cash tender off er if shareholders who retain stock will be harmed by the takeover. Part I of this Note examines the general background of the RICO Act. Part II applies the Act to a hostile cash tender offer and examines each element of a civil RICO action. Part III advocates the use of RICO\u27s injury requirement to limit this application of the Act and analyzes the potential injuries to shareholders and management during a hostile cash tender offer. This limitation upon the use of RICO conforms with the language and scope of the Act, as well as with the policies and current application of the federal securities laws

Lessons learnt from MyCyFAPP Project: Effect of cystic fibrosis factors and inherent-to-food properties on lipid digestion in foods

[EN] Unveiling mechanisms underpinning nutrient digestion has raised interest in the field of medical sciences for their potential application in clinical treatments. In the case of Cystic Fibrosis (CF), there exists an urgent need for understanding food lipid digestion to establish a criterion to adjust the dose of pancreatic enzyme supplements; patients have to take the supplements to allow digestion, given the associated exocrine pancreatic insufficiency (EPI). The aim of MyCyFAPP Project was to establish an evidence-based method to adjust pancreatic enzyme replacement therapy. To solve this challenge, the still unexplored field of real foods digestion had to be addressed. This review paper provides a description of the static in vitro digestion model that simulated different EPI intestinal conditions to conduct an extensive experimental work with 52 foods. Then, a summary of the data modelling that allowed for establishing a dosing criterion for enzyme supplements is provided. Following, by means of examples, an overview of the main findings related to the new knowledge generated in the field of lipid digestion in real foods is discussed, including the role of the inherent-to-food and the host factors affecting lipolysis. Finally, a discussion about the translation of the generated results in the lab to the clinical treatment of CF concludes with the lessons learnt from conducting this studyAuthors acknowledge the work and effort of the colleagues integrating MyCyFAPP Consortium for bringing knowledge and wisdom to this project. Especially, to those researchers significantly contributing to the field of in vitro digestion studies: Carolina Paz-Yepez, Victoria Fornes-Ferrer, Virginia Larrea, Irene Peinado, and Carmen Ribes-Koninckx. We acknowledge the Horizon 2020 Research and Innovation Framework Programme of the European Union for funding this project.Calvo-Lerma, J.; Asensio-Grau, A.; Heredia Gutiérrez, AB.; Andrés Grau, AM. (2020). Lessons learnt from MyCyFAPP Project: Effect of cystic fibrosis factors and inherent-to-food properties on lipid digestion in foods. Food Research International. 133:1-10. https://doi.org/10.1016/j.foodres.2020.109198S11013

The Role of preferences in logic programming: nonmonotonic reasoning, user preferences, decision under uncertainty

Intelligent systems that assist users in fulfilling complex tasks need a concise and processable representation of incomplete and uncertain information. In order to be able to choose among different options, these systems also need a compact and processable representation of the concept of preference. Preferences can provide an effective way to choose the best solutions to a given problem. These solutions can represent the most plausible states of the world when we model incomplete information, the most satisfactory states of the world when we express user preferences, or optimal decisions when we make decisions under uncertainty. Several domains, such as, reasoning under incomplete and uncertain information, user preference modeling, and qualitative decision making under uncertainty, have benefited from advances on preference representation. In the literature, several symbolic approaches of nonclassical reasoning have been proposed. Among them, logic programming under answer set semantics offers a good compromise between symbolic representation and computation of knowledge and several extensions for handling preferences. Nevertheless, there are still some open issues to be considered in logic programming. In nonmonotonic reasoning, first, most approaches assume that exceptions to logic program rules are already specified. However, sometimes, it is possible to consider implicit preferences based on the specificity of the rules to handle incomplete information. Secondly, the joint handling of exceptions and uncertainty has received little attention: when information is uncertain, the selection of default rules can be a matter of explicit preferences and uncertainty. In user preference modeling, although existing logic programming specifications allow to express user preferences which depend both on incomplete and contextual information, in some applications, some preferences in some context may be more important than others. Furthermore, more complex preference expressions need to be supported. In qualitative decision making under uncertainty, existing logic programming-based methodologies for making decisions seem to lack a satisfactory handling of preferences and uncertainty. The aim of this dissertation is twofold: 1) to tackle the role played by preferences in logic programming from different perspectives, and 2) to contribute to this novel field by proposing several frameworks and methods able to address the above issues. To this end, we will first show how preferences can be used to select default rules in logic programs in an implicit and explicit way. In particular, we propose (i) a method for selecting logic program rules based on specificity, and (ii) a framework for selecting uncertain default rules based on explicit preferences and the certainty of the rules. Then, we will see how user preferences can be modeled and processed in terms of a logic program (iii) in order to manage user profiles in a context-aware system and (iv) in order to propose a framework for the specification of nested (non-flat) preference expressions. Finally, in the attempt to bridge the gap between logic programming and qualitative decision under uncertainty, (v) we propose a classical- and a possibilistic-based logic programming methodology to compute an optimal decision when uncertainty and preferences are matters of degrees.Els sistemes intel.ligents que assisteixen a usuaris en la realització de tasques complexes necessiten una representació concisa i formal de la informació que permeti un raonament nomonòton en condicions d’incertesa. Per a poder escollir entre les diferents opcions, aquests sistemes solen necessitar una representació del concepte de preferència. Les preferències poden proporcionar una manera efectiva de triar entre les millors solucions a un problema. Aquestes solucions poden representar els estats del món més plausibles quan es tracta de modelar informació incompleta, els estats del món més satisfactori quan expressem preferències de l’usuari, o decisions òptimes quan estem parlant de presa de decisió incorporant incertesa. L’ús de les preferències ha beneficiat diferents dominis, com, el raonament en presència d’informació incompleta i incerta, el modelat de preferències d’usuari, i la presa de decisió sota incertesa. En la literatura, s’hi troben diferents aproximacions al raonament no clàssic basades en una representació simbòlica de la informació. Entre elles, l’enfocament de programació lògica, utilitzant la semàntica de answer set, ofereix una bona aproximació entre representació i processament simbòlic del coneixement, i diferents extensions per gestionar les preferències. No obstant això, en programació lògica es poden identificar diferents problemes pel que fa a la gestió de les preferències. Per exemple, en la majoria d’enfocaments de raonament no-monòton s’assumeix que les excepcions a default rules d’un programa lògic ja estan expressades. Però de vegades es poden considerar preferències implícites basades en l’especificitat de les regles per gestionar la informació incompleta. A més, quan la informació és també incerta, la selecció de default rules pot dependre de preferències explícites i de la incertesa. En el modelatge de preferències del usuari, encara que els formalismes existents basats en programació lògica permetin expressar preferències que depenen d’informació contextual i incompleta, en algunes aplicacions, donat un context, algunes preferències poden ser més importants que unes altres. Per tant, resulta d’interès un llenguatge que permeti capturar preferències més complexes. En la presa de decisions sota incertesa, les metodologies basades en programació lògica creades fins ara no ofereixen una solució del tot satisfactòria pel que fa a la gestió de les preferències i la incertesa. L’objectiu d’aquesta tesi és doble: 1) estudiar el paper de les preferències en la programació lògica des de diferents perspectives, i 2) contribuir a aquesta jove àrea d’investigació proposant diferents marcs teòrics i mètodes per abordar els problemes anteriorment citats. Per a aquest propòsit veurem com les preferències es poden utilitzar de manera implícita i explícita per a la selecció de default rules proposant: (i) un mètode basat en l’especificitat de les regles, que permeti seleccionar regles en un programa lògic; (ii) un marc teòric per a la selecció de default rules incertes basat en preferències explícites i la incertesa de les regles. També veurem com les preferències de l’usuari poden ser modelades i processades usant un enfocament de programació lògica (iii) que suporti la creació d’un mecanisme de gestió dels perfils dels usuaris en un sistema amb reconeixement del context; (iv) que permeti proposar un marc teòric capaç d’expressar preferències amb fòrmules imbricades. Per últim, amb l’objectiu de disminuir la distància entre programació lògica i la presa de decisió amb incertesa proposem (v) una metodologia basada en programació lògica clàssica i en una extensió de la programació lògica que incorpora lògica possibilística per modelar un problema de presa de decisions i per inferir una decisió òptima.Los sistemas inteligentes que asisten a usuarios en tareas complejas necesitan una representación concisa y procesable de la información que permita un razonamiento nomonótono e incierto. Para poder escoger entre las diferentes opciones, estos sistemas suelen necesitar una representación del concepto de preferencia. Las preferencias pueden proporcionar una manera efectiva para elegir entre las mejores soluciones a un problema. Dichas soluciones pueden representar los estados del mundo más plausibles cuando hablamos de representación de información incompleta, los estados del mundo más satisfactorios cuando hablamos de preferencias del usuario, o decisiones óptimas cuando estamos hablando de toma de decisión con incertidumbre. El uso de las preferencias ha beneficiado diferentes dominios, como, razonamiento en presencia de información incompleta e incierta, modelado de preferencias de usuario, y toma de decisión con incertidumbre. En la literatura, distintos enfoques simbólicos de razonamiento no clásico han sido creados. Entre ellos, la programación lógica con la semántica de answer set ofrece un buen acercamiento entre representación y procesamiento simbólico del conocimiento, y diferentes extensiones para manejar las preferencias. Sin embargo, en programación lógica se pueden identificar diferentes problemas con respecto al manejo de las preferencias. Por ejemplo, en la mayoría de enfoques de razonamiento no-monótono se asume que las excepciones a default rules de un programa lógico ya están expresadas. Pero, a veces se pueden considerar preferencias implícitas basadas en la especificidad de las reglas para manejar la información incompleta. Además, cuando la información es también incierta, la selección de default rules pueden depender de preferencias explícitas y de la incertidumbre. En el modelado de preferencias, aunque los formalismos existentes basados en programación lógica permitan expresar preferencias que dependen de información contextual e incompleta, in algunas aplicaciones, algunas preferencias en un contexto puede ser más importantes que otras. Por lo tanto, un lenguaje que permita capturar preferencias más complejas es deseable. En la toma de decisiones con incertidumbre, las metodologías basadas en programación lógica creadas hasta ahora no ofrecen una solución del todo satisfactoria al manejo de las preferencias y la incertidumbre. El objectivo de esta tesis es doble: 1) estudiar el rol de las preferencias en programación lógica desde diferentes perspectivas, y 2) contribuir a esta joven área de investigación proponiendo diferentes marcos teóricos y métodos para abordar los problemas anteriormente citados. Para este propósito veremos como las preferencias pueden ser usadas de manera implícita y explícita para la selección de default rules proponiendo: (i) un método para seleccionar reglas en un programa basado en la especificad de las reglas; (ii) un marco teórico para la selección de default rules basado en preferencias explícitas y incertidumbre. También veremos como las preferencias del usuario pueden ser modeladas y procesadas usando un enfoque de programación lógica (iii) para crear un mecanismo de manejo de los perfiles de los usuarios en un sistema con reconocimiento del contexto; (iv) para crear un marco teórico capaz de expresar preferencias con formulas anidadas. Por último, con el objetivo de disminuir la distancia entre programación lógica y la toma de decisión con incertidumbre proponemos (v) una metodología para modelar un problema de toma de decisiones y para inferir una decisión óptima usando un enfoque de programación lógica clásica y uno de programación lógica extendida con lógica posibilística.Sistemi intelligenti, destinati a fornire supporto agli utenti in processi decisionali complessi, richiedono una rappresentazione dell’informazione concisa, formale e che permetta di ragionare in maniera non monotona e incerta. Per poter scegliere tra le diverse opzioni, tali sistemi hanno bisogno di disporre di una rappresentazione del concetto di preferenza altrettanto concisa e formale. Le preferenze offrono una maniera efficace per scegliere le miglior soluzioni di un problema. Tali soluzioni possono rappresentare gli stati del mondo più credibili quando si tratta di ragionamento non monotono, gli stati del mondo più soddisfacenti quando si tratta delle preferenze degli utenti, o le decisioni migliori quando prendiamo una decisione in condizioni di incertezza. Diversi domini come ad esempio il ragionamento non monotono e incerto, la strutturazione del profilo utente, e i modelli di decisione in condizioni d’incertezza hanno tratto beneficio dalla rappresentazione delle preferenze. Nella bibliografia disponibile si possono incontrare diversi approcci simbolici al ragionamento non classico. Tra questi, la programmazione logica con answer set semantics offre un buon compromesso tra rappresentazione simbolica e processamento dell’informazione, e diversi estensioni per la gestione delle preferenze sono state proposti in tal senso. Nonostante ció, nella programmazione logica esistono ancora delle problematiche aperte. Prima di tutto, nella maggior parte degli approcci al ragionamento non monotono, si suppone che nel programma le eccezioni alle regole siano già specificate. Tuttavia, a volte per trattare l’informazione incompleta è possibile prendere in considerazione preferenze implicite basate sulla specificità delle regole. In secondo luogo, la gestione congiunta di eccezioni e incertezza ha avuto scarsa attenzione: quando l’informazione è incerta, la scelta di default rule può essere una questione di preferenze esplicite e d’incertezza allo stesso tempo. Nella creazione di preferenze dell’utente, anche se le specifiche di programmazione logica esistenti permettono di esprimere preferenze che dipendono sia da un’informazione incompleta che da una contestuale, in alcune applicazioni talune preferenze possono essere più importanti di altre, o espressioni più complesse devono essere supportate. In un processo decisionale con incertezza, le metodologie basate sulla programmazione logica viste sinora, non offrono una gestione soddisfacente delle preferenze e dell’incertezza. Lo scopo di questa dissertazione è doppio: 1) chiarire il ruolo che le preferenze giocano nella programmazione logica da diverse prospettive e 2) contribuire proponendo in questo nuovo settore di ricerca, diversi framework e metodi in grado di affrontare le citate problematiche. Per prima cosa, dimostreremo come le preferenze possono essere usate per selezionare default rule in un programma in maniera implicita ed esplicita. In particolare proporremo: (i) un metodo per la selezione delle regole di un programma logico basato sulla specificità dell’informazione; (ii) un framework per la selezione di default rule basato sulle preferenze esplicite e sull’incertezza associata alle regole del programma. Poi, vedremo come le preferenze degli utenti possono essere modellate attraverso un programma logico, (iii) per creare il profilo dell’utente in un sistema context-aware, e (iv) per proporre un framework che supporti la definizione di preferenze complesse. Infine, per colmare le lacune in programmazione logica applicata a un processo di decisione con incertezza (v) proporremo una metodologia basata sulla programmazione logica classica e una metodologia basata su un’estensione della programmazione logica con logica possibilistica

Answer Set Programming based on Propositional Satisfiability

Answer set programming (ASP) emerged in the late 1990s as a new logic programming paradigm that has been successfully applied in various application domains. Also motivated by the availability of efficient solvers for propositional satisfiability (SAT), various reductions from logic programs to SAT were introduced. All these reductions, however, are limited to a subclass of logic programs or introduce new variables or may produce exponentially bigger propositional formulas. In this paper, we present a SAT-based procedure, called ASPSAT, that (1) deals with any (nondisjunctive) logic program, (2) works on a propositional formula without additional variables (except for those possibly introduced by the clause form transformation), and (3) is guaranteed to work in polynomial space. From a theoretical perspective, we prove soundness and completeness of ASPSAT. From a practical perspective, we have (1) implemented ASPSAT in Cmodels, (2) extended the basic procedures in order to incorporate the most popular SAT reasoning strategies, and (3) conducted an extensive comparative analysis involving other state-of-the-art answer set solvers. The experimental analysis shows that our solver is competitive with the other solvers we considered and that the reasoning strategies that work best on ‘small but hard’ problems are ineffective on ‘big but easy’ problems and vice versa

Panterv. Marshall Field & Co.: The Good Faith Standard for Corporate Directors

Corporate directors traditionally have been immunized from liability for corporate actions involving questions of policy or business judgment, if such actions are taken in the exercise of due care, in good faith, and in compliance with applicable fiduciary duties. Judicial review of decisions made by corporate boards of directors in unsolicited takeovers generally has been barred by this business judgment rule. A recent challenge to this precept was brought in Panter v. Marshall Field & Co., a Seventh Circuit decision which highlighted many of the issues surrounding application of the business judgment rule in the context of a take-over attempt

In vitro study of cheese digestion: Effect of type of cheese and intestinal conditions on macronutrients digestibility

[EN] Exocrine Pancreatic Insufficiency (EPI) implies maldigestion, being pancreatic enzyme replacement therapy the treatment to enhance digestibility. This study aims at analysing the influence of cheese-related factors and intestinal conditions on macronutrients digestibility. Fresh-cow, fresh-goat, mild and aged cheeses were in vitro digested under different intestinal conditions of pH (6 or 7), bile concentration (1 or 10 mmol/L) and pancreatic enzymes (0-4000 LU/g fat) in order to in vitro mimic the intestinal conditions of a healthy adult and of an individual suffering of EPI. Under intestinal conditions of EN (pH 6, bile 1 mmol/L), lipids of fresh-goat and aged cheeses were more easily digested than those of fresh-cow and mild cheeses. In fact, 2000 LU/g fat of enzymatic dosage was enough to achieve a lipolysis extent of 80 and 100% in aged and fresh-goat cheeses, respectively. In contrast, proteolysis was higher in fresh-cow cheese and ripened (mild or aged) than in fresh-goat one regardless the intestinal conditions. Only in ripened-cheeses, proteolysis significantly increased at dose of enzymes does.Authors of this paper, on behalf of MyCyFAPP consortium, acknowledge the European Union and the Horizon 2020 Research and Innovation Framework Programme for funding the above-mentioned project under grant agreement number 643806. The authors would like to thank the Conselleria de Educacio i Investigacio de la Generalitat Valenciana for the PhD scholarship given to Andrea Asensio Grau.Asensio-Grau, A.; Peinado, I.; Heredia Gutiérrez, AB.; Andrés Grau, AM. (2019). In vitro study of cheese digestion: Effect of type of cheese and intestinal conditions on macronutrients digestibility. LWT - Food Science and Technology. 113:1-7. https://doi.org/10.1016/j.lwt.2019.108278S1711