Miracle-dz/UniFAR-FTUs huggingface dataset:
Hur ljuset påverkar könsmognad och äggläggning hos värphöns (Gallus domesticus)

Det ar sedan lange kant att om hons halls i naturlig belysning varierar agglaggningen med arstiderna. Lagst antal agg laggs nar dagarna ar som kortast och ljusstimuleringen ar som lagst. Eftersom honan reagerar aven pa artificiellt ljus kan ljusprogram anvandas for att styra antalet ljusa respektive morka timmar per dygn for att darigenom undvika arstidsvariation. Syftet med denna litteraturstudie ar att ta reda pa hur ljuset styr honans konsmognad och agg-laggning. Ljus registreras av fotoreceptorceller i retina, hypotalamus och epifysen vilka omvandlar energin i fotonerna till en biologisk signal. Vid ljusstimulering stimuleras gonadotropinfrisat-tande hormon (GnRH) vilket okar frislappningen av gonadotropinerna follikelstimulerande hormon (FSH) och luteiniserande hormon (LH). Ljusstimulering aktiverar aven inhibitoriska neuropeptider i hypotalamus som minskar GnRH-frislappningen. Sa lange ljusstimuleringen sker kommer okningen av GnRH-frislappning att radera effekten av de inhibitoriska neuro-peptiderna, men nar stimuleringen minskar tar den inhibitoriska effekten over och reproduk-tionsformagan minskar. Honans reproduktionsorgan bestar av aggstock och aggledare. Aggstockens funktion styrs av hypofysen, hypotalamus, epifysen och aggstockens egna hormonproducerande celler. Gonad-utveckling stimuleras av GnRH. Endast den vanstra aggstocken utvecklas till ett funktionellt organ. Den konsmogna aggstocken innehaller en hierarki av folliklar i olika utvecklings-stadier. Folliklarna tillvaxer kraftigt under den mognadsprocess som sker nar de utvecklas och upptar agguleprotein. I aggstocken omges aggcellen av tva cellager, thecaceller respektive granulosaceller. Thecaceller producerar androstenedion, som granulosacellerna konverterar till ostrogen. Ostrogen stimulerar inlagringen av agguleprotein fran levern. Granulosacellerna producerar aven progesteron, det hormon som initierar den kraftiga okning av LH som foregar ovuleringen. Ljus paverkar bade konsmognad och den fortsatta agglaggningen. Ratt ljus ar viktigt under hela agglaggningsperioden. For att en okad ljusstimulering ska ske vid en hojning av antalet ljustimmar maste antalet timmar overstiga en undre kritisk grans. Det finns aven en ovre mattnadsgrans dar en ytterligare hojning av antalet ljustimmar inte ger ytterligare stimulering. Hons har relativ ljusutmattning vilket innebar att deras kanslighet for ljusstimuli minskar over tid. I litteraturstudien beskrivs honans reproduktionsorgan, vilka hormoner som inverkar och hur ljusstimuli kan anvandas for att paverka konsmognad och aggproduktion. Min slutsats ar att ljus har en stor inverkan pa honans agglaggning. Bade antal ljustimmar per dygn, forandringar i ljusmonster over tid, ljusintensitet och ljusets vaglangd har visat sig paverka agglaggningen. Aven om det bedrivits intensiv forskning under lang tid pa olika aspekter av hur ljuset paver-kar honans agglaggning finns det ett behov av ytterligare forskning, exempelvis pa hur lag-energibelysning bor vara utformad for att efterlikna dagsljuset pa basta mojliga satt.
Portable Unmanned Aircraft System Concept Investigation

Abstract : This report investigates the feasibility of a portable unmanned aircraft system (PUMA) for deployment in various close range (up to 30 km) reconnaissance and surveillance missions, which would provide a capability, estimated to be 50 to 60% of the performance of much larger and significantly more expensive systems. The PUMA would have a total mass of 10-12 kg and a 3 kg electrically powered flying wing configuration, which could be launched by a rubber bungee and captured by either a net or a special arrestor. The primary sensor would be a charge coupled device camera with either a second or third generation image intensifier. Navigation and control of the vehicle could be performed by an inexpensive attitude and heading reference system combined with a small global positioning system receiver. Data would be transmitted over very high frequency channels, which could be accomplished by employing data compression techniques.
Delivery Date Decision Support System for the Large Scale Make-to-Order Manufacturing Companies: An Electric Motor Company Case

In the make-to-order (MTO) manufacturing environment, one of the important issues is setting attainable delivery dates for customer orders, which significantly affects the performance of the MTO manufacturing. Although this topic has received considerable attention in the literature, most of the efforts took a lower level approach that is concerned primarily with the effect of various delivery date assignment methods on the relative performance of some dispatching rules. This paper proposes the delivery date decision support system which takes a higher level approach of integrating the marketing and production planning functions with the consideration of the current capacity and the workload smoothing. The proposed system has been implemented in a Rotating Machinery Shop and the results of the implementation showed good performance.
Magellan: A Personalized Travel Recommendation System Using Transaction Data

We present Magellan - a personalized travel recommendation system that is built entirely from card transaction data. The data logs contain extensive metadata for each transaction between a user and a merchant. We describe the procedure employed to extract travel itineraries from such transaction data. Unlike traditional approaches, we formulate the recommendation problem into two steps: (1) predict coarse granularity information such as location and category of the next merchant; and (2) provide fine granularity individual merchant recommendations based on the predicted location and category. The breakdown helps us build a scalable recommendation system. We propose a quadtree-based algorithm that provides an adaptive spatial resolution for the location classes in our first step while also reducing the class-imbalance across various location labels. Finally, we propose a novel neural architecture, SoLEmNet, that implicitly learns the inherent class label hierarchy and achieves a higher performance on our dataset compared to previous baselines.
Conditional Random Fields for Biomedical Named Entity Recognition Revisited

Named Entity Recognition (NER) is a key task which automatically extracts Named Entities (NE) from the text. Names of persons, places, date and time are examples of NEs. We are applying Conditional Random Fields (CRFs) for NER in biomedical domain. Examples of NEs in biomedical texts are gene, proteins. We used a minimal set of features to train CRF algorithm and obtained a good results for biomedical texts.
Análise de Dados em Redes Sem Fio de Grande Porte: Processamento em Fluxo em Tempo Real, Tendências e Desafios

In this chapter, we focus on knowledge extraction from large wireless networks through stream processing. We present the primary methods of sampling, data collection and monitoring of wireless networks and we characterize knowledge extraction as a machine learning problem on big data stream processing. The Apache Spark and Apache Flink are the main trends on big data stream processing frameworks and, thus, are discussed in this chapter. We explore the data preprocessing, the feature engineering and the machine learning algorithms applied to the scenario of wireless network analytics. We address challenges and research projects in wireless network monitoring and stream processing. Finally, future perspectives, such as deep learning and reinforcement learning in stream processing, are anticipated.
Fast Channel Allocation for Ultra-dense D2D-enabled Cellular Network with Interference Constraint in Underlaying Mode

We investigate the channel allocation problem in an ultra-dense device-to-device (D2D) enabled cellular network in underlaying mode where multiple D2D users are forced to share the same channel. Two kinds of low complexity solutions, which just require partial channel state information (CSI) exchange, are devised to resolve the combinatorial optimization problem with the quality of service (QoS) guaranteeing. We begin by sorting the cellular users equipment (CUEs) links in sequence in a matric of interference tolerance for ensuring the SINR requirement. Moreover, the interference quota of CUEs is regarded as one kind of communication resource. Multiple D2D candidates compete for the interference quota to establish spectrum sharing links. Then base station calculates the occupation of interference quota by D2D users with partial CSI such as the interference channel gain of D2D users and the channel gain of D2D themselves, and carries out the channel allocation by setting different access priorities distribution. In this paper, we proposed two novel fast matching algorithms utilize partial information rather than global CSI exchanging, which reduce the computation complexity. Numerical results reveal that, our proposed algorithms achieve outstanding performance than the contrast algorithms including Hungarian algorithm in terms of throughput, fairness and access rate. Specifically, the performance of our proposed channel allocation algorithm is more superior in ultra-dense D2D scenarios.
Exploring the cornerstone of Wal-Mart's success and competitiveness

Sam Walton opened his first Wal‐Mart discount store in 1962. Today, Wal‐Mart is not only the world’s largest corporation but also the world’s most admired company, according to a 2003 Fortune magazine poll. Wal‐Mart is competitive and successful because it has been doing many things right. This article helps shed light on the rise of Wal‐Mart and the roots of its competitiveness. Business practitioners aspiring to succeed can learn a great deal from studying the Wal‐Mart way of doing business.
Transformation of the Restaurant Business as a Result of the COVID-19 Pandemic: Improving the Security of Service and Maintaining the Health of Human Capital

The study identified socio-economic problems in the restaurant business, analyzed the dynamics of its decline and recovery during the pandemic COVID-19, considered innovative trends in the transformation of restaurant management. Systematization of literature sources and approaches to the study of the impact of epidemics and pandemics on restaurant activities showed that until 2019, cases of infection of restaurant visitors occurred. However, they were isolated or local (regional) in nature and attracted the attention of most medical researchers. The COVID-19 pandemic is global in heart and has affected all economic areas, including the restaurant industry. Therefore, the number of scientific papers in this field is proliferating. The urgency of solving the scientific problem is that during the COVID-19 pandemic, restaurant customers’ behavior and a significant increase in the number of online orders. This encourages restaurants to respond and transform their business models, business strategies and diversify sales channels. The research method is based on the statistical analysis of restaurant business performance indicators at the global level and the level of Ukraine and the analysis of innovative modern trends in the transformation of the restaurant business. The study results showed that the restaurant industry’s main problems in the period of quarantine restrictions and lockdowns are mass layoffs, declining sales, inability to adapt and transform to the new conditions of the restaurant business. Accordingly, the directions of transformation of the restaurant business based on breakthrough innovations to increase customer service safety during the pandemic are proposed. The article focuses on the possibilities of restaurants to promote the health of human capital by diversifying the menu for vulnerable groups, such as children, people with chronic diseases, members of certain racial and ethnic minorities, the elderly. The results of this study can help build a policy in the restaurant industry to overcome the crisis in this area and improve public health. Also, the results can be used by restaurants to increase their competitiveness based on specific transformation measures.
Economic Impacts of Bt Cotton Adoption: A National and Regional Assessment

This study uses a quadratic programming model to estimate impacts of Bt cotton adoption on consumer benefits, cotton program outlays, and producer returns, by state and by grower adoption status. Three scenarios were considered simulating low, moderate, and high impacts of Bt cotton adoption. For the moderate impact scenario, U.S. benefits from Bt cotton adoption grew from $44 million in 1996 to $66 million in 1998. Annual U.S. consumer benefits ranged from $46– $55 million. Benefits to Bt adopters grew from $57 million in 1996 to $97 million in 1998. Losses to non-adopters fell from -$59 million in 1996 to -$8 million in 1998 as rising commodity program payments countered the impact of lower prices. In 1998, gains to Arizona Bt cotton adopters (net of adoption costs) were about $9 million, averaging over $15,000 per adopting farm.
Drill Baby, Drill! : An Analysis of Late Period Chumash Microdrills from CA-SLO-214

This thesis research focuses on a curated CRM collection of Late Period Chumash chert microdrills from CA-SLO-214. The main goal of this research is to compare the Chumash drill-making industry in Los Osos to the known industry on the Channel Islands. A literature review was conducted on both Chumash mainland and island microdrills. Laboratory analysis focused exclusively on the collection of microdrills from Los Osos in order to compare the less studied Northern Chumash microdrills to the documented Santa Cruz Island microdrills. This research shows that the Northern Chumash m~de and used chert microdrills. These tools have been found on the coast near Los Osos and inland in San Luis Obispo. These Northern Chumash microdrill types are very similar to each other, but dissimilar to microdrill types found further south near Gaviota, and very different than the microdrills on Santa Cruz Island. I show that the Northern Chumash had a microdrill production industry dissimilar in technology, intensity, and wear patterns to their southern counterparts, but have similar dimensions. The presence of these tools in this area may suggest a higher degree of social complexity than has been previously thought. MA ogram: Cultural Resources Management Sonoma State University Date: ~
Enlistment Effects of the 2+2+4 Recruiting Experiment

Abstract : This report describes the enlistment effects of the 2+2+4 recruiting experiment. The 2+2+4 program is a new Army recruiting incentive aimed at attracting high-quality personnel into the active Army and encouraging their later participation in the reserves. The program offers qualified recruits an additional option, beyond the normal set of enlistment benefits and choices: they may receive the Army College Fund (ACF) if they enter an eligible specialty for a two-year term of active service, provided that they agree to serve an additional two-year term in the Selected Reserve. This program was tested in a national experiment from July 1989 through September 1990.
Static, dynamic and levitation characteristics of squeeze film air journal bearing : designing, modelling, simulation and fluid solid interaction

Bearings today need to be able to run at very high speed, providing high positional accuracy for the structure that it supports, and requiring very little or no maintenance. For this to happen, bearings must have tight tolerances and very low or zero friction during operation. This pushes many traditional contact-type bearings to their limits as they often fail due to friction, generating heat and causing wear. By comparison, existing non-contact bearings fare better because of their very low or zero friction. But some have their own problem too. For example, the fact that aerostatic bearings require an air supply means having to use a separate air compressor and connecting hoses. This makes the installation bulky. Aerodynamic and hydrodynamic bearings cannot support loads at zero speed. Both hydrodynamic and hydrostatic bearings may cause contamination to the work-pieces and the work environment because of the use of lubricating fluid. A potential solution to the above-mentioned problems is the new squeeze film air bearing. It works on the rapid squeeze action of an air film to produce separation between two metal surfaces. This has the benefit of being compact with a very simple configuration because it does not require an external pressurized air supply, can support loads at zero speed and is free of contamination. For this research, two squeeze film air journal bearings, made from material of Al 2024 – T3 and Cu C101 with the same geometry, were designed. The bearing is in the shape of a round tube with three fins on the outer surface and the journal, a round rod. When excited at a certain normal mode, the bearing shell flexes with a desirable modal shape for the squeeze film action. The various modes of vibration of Al bearing were obtained from a finite-element model implemented in ANSYS. Two Modes, the 13th and 23rd, at the respective frequencies of 16.320 kHz and 25.322 kHz, were identified for further investigation by experiments with respect to the squeeze film thickness and its load-carrying capacity. For Cu bearing, the two Modes are also 13th and 23rd at the respective frequencies of 12.184 kHz and 18.459 kHz. Abstract
Evolvable neural networks ensembles for accidents diagnosis

Prediction and diagnosis of nuclear accidents is one of the most important tasks for nuclear safety. Since accurate diagnosis of nuclear accident is a very important issue for avoidance of disastrous outcomes, it is more desirable to make a decision by combining the results of various expert classifiers rather than by depending on the results of only one classifier. To deal with such challenging problem, the idea of using ensemble classifiers to predict and diagnose accidents is proposed in this paper. Ensembles improve both the efficiency in learning the model and the accuracy in performing classification. Ensemble classifier has substantial advantage over single classifier in prediction accuracy, and the ensemble framework is effective for a variety of classification models. A new method to design and evolve neural network ensembles NNEs based on speciation is used classify reactor data. The main advantage of this method is that, it completely evolves NNEs by combining the evolution of neural networks and the configuration of the ensemble in one evolutionary phase. After forming the ensemble, several accident diagnoses were performed. The results indicate that ensemble able to diagnose the accidents accurately with high rate.
Handbook of Position Location: Theory, Practice and Advances

Radio systems capable of localization have emerging applications in homeland security, law enforcement, emergency response, defense command and control, multi-robot coordination and vehicle-to-vehicle and vehicle-to-pedestrian collision avoidance. In fact, high resolution localization is vital for many applications, including: traffic alert, emergency services, e.g., indoor localization for firefighters, and battlefield command and control. These systems promise to dramatically reduce society's vulnerabilities to catastrophic events and improve its quality of of life.While work this important area is progressing, limited resources are available to support graduate students and researchers in this important area. Specifically, a limited number of books has been published in this area covering selected subjects. This comprehensive handbook offers gaps of available localization books presenting in-depth coverage from fundamentals of coordinates to advanced application examples.
An Empirical Study on Management Practices in Cooperative Sugar Factories of Gujarat

The cooperative sugar factories are agri business units incorporated under cooperative form of business organizations in Gujarat. Sugar being an essential commodity, this industry enjoys the benefits of ‘sellers markets’. They aren’t required to go out in the market in search of customers. In this industry the competition is for raw materials as there are several alternatives uses of the cane sugar. The mind sets of management and employees of this industry is more ‘production oriented’ rather than ‘productive oriented’ and thus management function is being practiced merely as an administrative function rather than the strategic one. Since long researchers, practitioners and policy makers have studied various technical aspects of this industry from time to time so as to increase the production efficiency of sugarcane and sugar. However there is paucity of research on management aspects of this industry. In modern times ‘management' is being treated as a technology and one of the most fundamental factor of production. Thus in this paper the researcher wants to study and know the various professional practices and procedures of management adopted in managing the cooperative sugar factories of Gujarat.
Induction Suspension of Conductive Microring and Its Gyroscopic Stabilization

The main task of our work is determination of possible levitation of micro-ring with eddy current in magnetic field of down ring with set alternating current and determination of critical value of «ohmic» damping separated field of parameters, at which motions of suspension ring transit from divergent to meeting to steady-state equilibrium position. I. e. in this critical case the motion practically coincides with motions of conservative system. The possibility of gyroscopic stabilization of suspension ring taking into account initial set rotation is considered. Thereby it can serve as contactless micro-gyroscope.
8 Reduced-order modeling for applications to the cardiovascular system

: The capability to provide fast and reliable numerical simulations is of paramount importance when dealing with complex applications arising from medi-cine. More than for other branches of engineering and applied sciences, performing accurate computations in a short amount of time – minutes, rather than hours, or even days – is crucial when dealing with problems arising from life sciences, like, e. g. , in the simulation of the cardiovascular system. Moreover, many sources of variability carried by subject-specific features have to be incorporated into the mathematical models, to quantify their impact on the computed results. For these reasons, bringing computational results into clinical practice represents a great challenge. Reduced-order modeling techniques such as the reduced basis method represent a key tool towards the possibility to address these challenges, thus making the numerical modeling of the cardiovascular system a new, fascinating testbed for these methodologies.
Negation Detection on Mexican Spanish Tweets: The T-MexNeg Corpus

In this paper, we introduce the T-MexNeg corpus of Tweets written in Mexican Spanish. It consists of 13,704 Tweets, of which 4895 contain negation structures. We performed an analysis of negation statements embedded in the language employed on social media. This research paper aims to present the annotation guidelines along with a novel resource targeted at the negation detection task. The corpus was manually annotated with labels of negation cue, scope, and, event. We report the analysis of the inter-annotator agreement for all the components of the negation structure. This resource is freely available. Furthermore, we performed various experiments to automatically identify negation using the T-MexNeg corpus and the SFU ReviewSP-NEG for training a machine learning algorithm. By comparing two different methodologies, one based on a dictionary and the other based on the Conditional Random Fields algorithm, we found that the results of negation identification on Twitter are lower when the model is trained on the SFU ReviewSP-NEG Corpus. Therefore, this paper shows the importance of having resources built specifically to deal with social media language.