Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision-Making Capacity in Patients with Alzheimer ’ s Disease : A Systematic Review

The capacity to make decisions is an important feature of daily living, which is closely linked to proper cognitive functioning. In conditions in which cognitive functioning becomes compromised, such as in Alzheimer’s disease (AD), decision-making capacity can also get affected. Especially in AD, this has important implications, since over the course of the condition many important clinical decisions have to be made. For caregivers as well as physicians, it is sometimes difficult to determine how and when to intervene in the decision-making process. The aim of this systematic literature review was to identify studies that have evaluated medical and research consent decision-making capacity in patients with AD. Studies consistently show that decision-making capabilities are impaired in patients with AD. The cognitive and neuronal correlates of this process are, however, poorly studied. The few studies that investigated correlations have shown worse cognitive performance, mainly on the MMSE, to be related to poorer decision-making capacity. As most of these correlations have been performed in groups combining patients and controls, it remains unknown if these associations are disease specific. There is a need to study more systematically the decision-making process in relation to cognitive functioning and neural correlates to be able to develop a framework of decision-making capacity in AD, ultimately aiding clinicians and caregivers to understand and evaluate those capabilities in patients. 15
Spatiotemporal-Coherent Semantic Maps for Advanced Robot Navigation

In this paper we introduce a novel online semantic mapping framework apt to establish the seamless cooperation between the low level geometrical information and the high level environment’s perception. Its main contribution involves the online formation of a semantic map, relying on the memorization of abstract place representations and capitalizing both on space quantization and time proximity. A time evolving Augmented Navigation Graph is formed describing the semantic topology of the explored environment and the connectivity among the places visited, which is expressed as the interplaces transition probability. A side contribution of this paper involves the utilization of the learned semantic maps for efficient navigation in the explored environment. Moreover, a specific human-robot interaction paradigm is proposed by illustrating a competent methodology to address the go-to tasks. The performance of the proposed framework was evaluated on long range robot datasets in an unstructured office environment and it exhibits remarkable performance by inferring semantic maps in previously unexplored environments.
INFORMATION DISCLOSURE BY CHARITY ORGANIZATIONS

This study is an empirical investigation on the extent of disclosure of information by charity organizations in Malaysia. It also reports the association between organizational-specific attributes and the extent of disclosure. Using content analysis, a total of 88 items of information listed in disclosure index were applied to 65 annual returns for the year 2009 of charity organizations. The study revealed a very low level of disclosure of information, with a mean score of only 23.98. The findings also found that the existence of an independent audit is highly significant and positively related to the extent of disclosure. Similarly, the organizationalspecific attributes such as organizational size and financial performance are also found to be significant. Other variables such as age, board size and board composition are insignificant in explaining the extent of disclosure. This study has contributed to the academic literature, showing that the existence of external governance mechanism brings the potential for better disclosure and transparency. This disclosure is at least sufficiently meets the requirement of the Registry. This study could assist in better understanding of how to improve the extent of disclosure for the charity organizations.
Fast and Resilient Indoor Floor Plan Construction with a Single User

A lack of floor plans is a fundamental obstacle to ubiquitous indoor location-based services. Recent work have made significant progress to accuracy, but they largely rely on slow crowdsensing that may take weeks or even months to collect enough data. In this paper, we propose Knitter that can generate accurate floor maps by a single random user’s one hour data collection efforts, and demonstrate how such maps can be used for indoor navigation. Knitter extracts high quality floor layout information from single images, calibrates user trajectories, and filters outliers. It uses a multi-hypothesis map fusion framework that updates landmark positions/orientations and accessible areas incrementally according to evidences from each measurement. Our experiments on three different large buildings (up to <inline-formula><tex-math notation="LaTeX">$140\times 50\;\mathrm{m}^2$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>140</mml:mn><mml:mo>×</mml:mo><mml:mn>50</mml:mn><mml:mspace width="0.277778em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:math><inline-graphic xlink:href="gao-ieq1-2857813.gif"/></alternatives></inline-formula>) with 30+ users show that Knitter produces correct map topology, with landmark location errors of <inline-formula><tex-math notation="LaTeX">$3\sim 5\;\mathrm{m}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>3</mml:mn><mml:mo>∼</mml:mo><mml:mn>5</mml:mn><mml:mspace width="0.277778em"/><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="gao-ieq2-2857813.gif"/></alternatives></inline-formula> and orientation errors of <inline-formula><tex-math notation="LaTeX">$4\sim 6^\circ$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>4</mml:mn><mml:mo>∼</mml:mo><mml:msup><mml:mn>6</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math><inline-graphic xlink:href="gao-ieq3-2857813.gif"/></alternatives></inline-formula>, both at 90-percentile. Our results are comparable to the state-of-the-art at more than <inline-formula><tex-math notation="LaTeX">$20\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>20</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="gao-ieq4-2857813.gif"/></alternatives></inline-formula> speed up: data collection in each of the three buildings can finish in about one hour even by a novice user trained just a few minutes.
A Distributional Semantic Model of Visually Indirect Grounding for Abstract Words

Recent studies on abstract words have proposed an indirect grounding view that abstract words are grounded indirectly through linguistic interdependency among amodal and modal symbols. In this paper, we model the indirect grounding view by means of multimodal distributional semantics. In the proposed model, an abstract word is represented by both its textual vector and the visual vectors of its semantically related concrete words. A simulation experiment demonstrated that the indirect grounding model achieved better performance in predicting human conceptual representation of abstract words. This finding indicates the plausibility of indirect grounding as a cognitive mechanism of representing abstract words.
Measuring innovation culture in organizations The development of a generalized innovation culture construct using exploratory factor analysis

Purpose – Academic and practitioner interest has focused on innovation as a method of competitive differentiation and as a way to create customer value. However, less attention has been devoted to developing a measure of innovation culture. The purpose of this paper is to develop an empirically-based comprehensive instrument for measuring an organization’s innovation culture. Design/methodology – This paper describes a procedure which explicates the innovation culture construct, and proposes a multi-item measure of innovation culture predicated on exploratory factor analysis. These descriptors were derived from extant literature, key informant interviews, and a survey of over 282 employees from the financial services industry. Findings – Findings suggest that an innovation culture scale may best be represented through a structure that consists of seven factors identified as innovation propensity, organizational constituency, organizational learning, creativity and empowerment, market orientation, value orientation, and implementation context. Practical implications – The seven-factor model can be used both descriptively and diagnostically. Among other things, it presents a practical way to measure an organization’s innovation culture, and could initially be used to establish a baseline level of innovation culture. From there, it could be used as a metric to chart the organization’s efforts as it moves to engender innovation. Originality/value – More effort should be devoted to developing measures to assess innovation culture specifically. This model presents an innovation culture construct that is complimentary to work that has preceded it. The findings combined with the suggestions provide an alternative perspective as a measure of innovation and extends a basic framework for further investigation.
Deep Sparse Autoencoders for American Sign Language Recognition Using Depth Images

In this paper we address the problem of hand gestures recognition in the American Sign Language using machine learning. We propose a five layer unsupervised encoder-decoder neural model. We use a dataset of segmented images captured with a depth-sensor camera for different subjects. The average accuracy obtained was of 98.9% and as high as 99.4% on unseen data.
TOWARD A FLIP-CHIP BONDER DEDICATED TO DIRECT BONDING FOR PRODUCTION ENVIRONMENT

3D vertical integration of components is now an industrial reality. To reduce interconnection pitch between the various dies, the hydrid bonding technique, which can offer sub-10μm interconnection pitch, is widely demonstrated for Wafer-to-Wafer bonding. Die-to-Wafer direct bonding remains today more challenging due to additional particle contamination and handling complexity. The purpose of this paper is to demonstrate the performance of a fully automated Die-to-Wafer bonder, SET FC1, specifically designed for direct bonding. After a description of the elements developed specially for direct bonding (loader.), it will be demonstrated that a throughput up to 500 dph (dies per hour) with an accuracy of ± 1μm can be reached today. If progresses still need to be done, the particle contamination is low enough to enable the 1 demonstration of oxide/oxide Die-to-Wafer direct bonding. First results with dummy dies are promising with similar alignment accuracy and significant improvement of the throughput compared to previous equipment SET FC300. These performances have been confirmed on bare dies. If these results are very encouraging, current tests are ongoing with copper/oxide patterned dies. Trade-off between short cycle time and high bonding precision seems less crucial and industrialization appears feasible.
Making mini-grids work Productive uses of electricity in Tanzania

of projects proposed by the E4I (GVEP) for investors on Ukara Island ICE BLOCk PROdUCTIOn: OvERvIEW OF ThE OPPORTUnITy Key project features • Project description: creation of an operating company in charge of producing iceblocks in Ukara commercially • Land plot to be awarded for lease
Rule-Based Sentence Quality Modeling and Assessment using Deep LSTM Features

People trying to master the art of writing correct sentences in English for the first time often find themselves in the struggle of learning the essential rules to do so. In an effort to assist in this process we studied how to represent a sentence with the purpose of analyzing its quality according to wellknown rules. We make use of recent developments in deep learning to achieve a rich representation of single sentences, commonly known as embedding [1]. Sentence quality has been traditionally evaluated in the context of machine translation to measure success [2, 3]. However, our work measures the quality of a sentence as the end product of the model. Recently, recurrent neural networks (RNNs) with long-short term memories (LSTMs) have been used for word embedding [4], sentence embedding [5], and paragraph or document embedding [6] with very good results. These works have demonstrated the utility and robustness of finding discriminative vectorial representations that preserve context and major structures of words and bodies of text. Thus, we decided to study their utility in modeling and assessing the overall quality of individual sentences.
Zero-Shot Image Classification Guided by Natural Language Descriptions of Classes : A Meta-Learning Approach

We propose a model that learns to perform zero-shot image classification from natural language descriptions by using a meta-learner that is trained to produce a correction to the output of a previously trained learner. The model consists of two modules: a task module (learner) that supplies an initial prediction, and a correction module (meta-learner) that updates the initial prediction. The correction module is trained in an episodic approach whereby many different task modules are trained on various subsets of the total training data, with the rest being used as unseen data for the correction module. The correction module takes as input a representation of the task module’s training data so that the predicted correction is a function of the task module’s training data. The correction module is trained to update the task module’s prediction to be closer to the target value. This approach leads to state-of-the-art performance for zero-shot classification on natural language class descriptions on the CUB and NAB datasets.
An Ant Colony Optimization Routing Strategy for Wireless Sensor Networks : A SDN-like Perspective

Software defined networking (SDN) provides the advantages of decoupling the control and the forwarding planes and the packets are classified into flows and the routing decision are based on the flow. Since the SDN conducts the flow-based routing strategy and ant colony optimization (ACO) routing protocols have the potential to work in a flow-based manner. Previous research of ant-based routing algorithms mainly focused on energy efficiency. However, how ant-based routing algorithms perform in other metrics has been neglected. In this research, we compare the packet delivery ratio, the end-to-end delay and the first packet arrival time of an ant colony optimization (ACO) routing algorithm with three routing protocols, namely, AODV, DSDV, and DSR, in the wireless sensor networks with different density traffic. We found that the ACO is not only energy efficient but also has the best performance in both the packet delivery ratio and the first packet arrival time compared to other routing algorithms with low density traffic. In some low density traffic cases, it might not perform well in the end-to-end delay. The ACO does not perform well in both the packet delivery ratio and the end-to-end delay with high density traffic, so ACO is more suitable to be used in low density traffic.
S ep 2 01 9 Families of magnetic semiconductors-an overview

The interplay of magnetic and semiconducting properties has been in the focus since more than a half of the century. In this introductory article we briefly review the key properties and functionalities of various magnetic semiconductor families, including europium chalcogenides, chromium spinels, dilute magnetic semiconductors, dilute ferromagnetic semiconductors and insulators, mentioning also sources of non-uniformities in the magnetization distribution, accounting for an apparent high Curie temperature ferromagnetism in many systems. Our survey is carried out from today’s perspective of ferromagnetic and antiferromagnetic spintronics as well as of the emerging fields of magnetic topological materials and atomically thin 2D layers.
A Case of Thoracoscopic Wedge Lung Resection of Small-sized Ground-glass Nodules Using Virtual-assisted Lung Mapping

━━ Background. It has recently been suggested that virtual-assisted lung mapping (VAL-MAP) may enable more reliable and safer intraoperative navigation than conventional preoperative lung marking strategies. We herein report a case of thoracoscopic wedge lung resection of small-sized ground-glass nodules (GGNs) using VAL-MAP. Case. A 63-year-old man who had undergone treatment for prostate cancer presented with two smallsized peripheral GGNs in the right upper lobe. A follow-up chest CT scan of the patient nine months later demonstrated an increase in the size of the two GGNs. Due to the patient’s severe renal insufficiency, we decided to perform thoracoscopic wedge lung resection using VAL-MAP. Intraoperatively, four blue markings were clearly visible on the right upper lobe, and the two lesions were successfully resected with single wedge resection along the markings as Merkmal. The pathological diagnosis was adenocarcinoma in situ. The patient’s postoperative course was uneventful, and he remains well after one year, with no evidence of recurrence. Conclusions. We herein reported a case of thoracoscopic wedge lung resection of small-sized GGNs that was performed using VAL-MAP. VAL-MAP is a novel and useful strategy for detecting small-sized peripheral lung lesions with a high degree of reliability and safety. (JJLC. 2015;55:206-211) KEY WORDS━━ Virtual-assisted lung mapping (VAL-MAP), Ground-glass nodule (GGN), Wedge lung resection, Adenocarcinoma in situ Received February 5, 2015; accepted June 1, 2015. 要旨━━背景. 従来の術前肺マーキング法と異なり,複 数個所にマーキングを施し,肺に「地図」を描くバーチャ ル気管支鏡ナビゲーションを利用した術前気管支鏡下肺 マッピング法(VAL-MAP)には,より確実・安全な手術 支援が期待される. VAL-MAPを用い,微小なGGNに対 して完全鏡視下切除を行った症例を報告する. 症例. 63 歳男性. 前立腺癌の術前精査のために撮影された胸部 CTで,右肺上葉の胸膜直下にGGNを 2ヵ所指摘され, 当科紹介となった. 9ヵ月後の胸部CTで GGNの増大を 認め,手術による切除の方針とした. 末期腎不全患者で あり,VAL-MAPを用いた肺部分切除の適応とした. 手 術は 3ポートによる完全鏡視下手術で行った. 右肺上葉 に 4ヵ所のマーキングを確認し,それらをメルクマール とし,2つの病巣をそれぞれ部分切除した. それぞれの切 除標本内に病変を確認し,手術終了とした. 術後経過は 良好であった. 永久病理診断はともに adenocarcinoma 1公益財団法人田附興風会医学研究所北野病院呼吸器外科;2京 都大学医学部呼吸器外科. 受付日:2015 年 2 月 5 日,採択日:2015 年 6 月 1 日. (肺癌.2015;55:206-211) 2015 The Japan Lung Cancer Society Wedge Resection of Small-sized Ground-glass Nodule Using Virtual-assisted Lung Mapping―Yamanashi et al Japanese Journal of Lung Cancer―Vol 55, No 4, Aug 20, 2015―www.haigan. gr.jp 207 Figure 1. Chest CT showed two small-sized peripheral ground-glass nodules (S1; 4 mm in diameter, S2; 8 mm in diameter). in situであった. 術後 1年現在,再発なく経過観察中であ る. 結論. 従来の術前肺マーキング法と比較してVALMAPは,確実性と安全性を兼ね備えた有用なマーキン グ法であると考えられる. 索引用語━━ Virtual-assisted lung mapping ( VALMAP),Ground-glass nodule(GGN),肺部分切除,Ade-
Captcha as Textual Passwords with Click Points to Protect Information

Most of the proposed graphical authentication system has certain drawbacks for that reason textual passwords are most preferable authentication system where users type passwords to authenticate themselves. An important usability goal of an authentication system is to support users for selecting the better password. User creates memorable password which is easy to guess by an attacker and strong system assigned passwords are difficult to memorize. So researchers of modern days gone through different alternative methods and conclude that graphical passwords are most preferable authentication system because graphical passwords are easy to remember but the problem these authentication system is prone to shoulder surfing attacks. The proposed system combines the existing textual passwords encryption and captcha password with different algorithms and added with click points to protect information, encouraging user to select more random click point which is difficult to guess. Proposed system is not a panacea, but it offers reasonable security and usability and appears to fit well with some practical applications for improving online security and also provide more protection against online dictionary attacks. Keywords— Authentication, textual passwords, captcha, usable security, click points, dictionary attacks
CORRELATES OF ACADEMIC PROCRASTINATION OF STUDENT TEACHERS WITH THEIR PEDAGOGICAL COMPETENCE

Occurrence of Academic procrastination is a widespread phenomenon that results in a range of negative outcomes. Many studies determined causes and correlates of academic procrastination among school children; yet, the study on student teachers for academic procrastination is limited. The present study is aimed at examining correlation between academic procrastination and pedagogical competence of student teachers as a base for developing an intervention for academic procrastination. Academic procrastination assessment scale and pedagogical competence scale developed by investigators were used to determine the significant differences and correlation of academic procrastination and pedagogical competence among student teachers. Findings depicted that 48.3% of student teachers out of 840 are seemed to have a moderate level of academic procrastination. It is also found that male student teachers scored high in academic procrastination scale as they are tend to be highly procrastinated than their counterparts while female student teachers scored high on pedagogical competence than males. Correlation analysis showed that academic procrastination and pedagogical competence of student teachers are highly correlated. Results supported the notion that academic procrastination is a barrier to student teachers’ academic outcomes and elucidates the need to develop academic interventions to lessen procrastination behaviours as a way to decrease its predominance in academic settings.
Studying the Intervention of an Unusual Term in f ( T ) Gravity via Noether Symmetry

As usual, we observe an unknown coupling function, i.e. F (φ) , with a function of torsion and also curvature, i.e. f(T ) and f(R) , generally depending on a scalar field. In f(R) case, it comes from quantum correlations and other reasons. Now, what if beside this term in f(T )-gravity context, we enhance the action through another term which depends on both scalar field and its derivatives? In this paper, we have added such an unprecedented term in the generic common action of f(T )-gravity such that in this new term, an unknown function of torsion has coupled with an unknown function of both scalar field and its derivatives. We have explained why we can append such term, in the introduction in details. By the use of Noether symmetry approach, we have considered its behavior and effect. We have shown that it does not produce an anomaly, but rather it works successfully and numerical analysis of the exact solutions of field equations coincide with all most important observational data particularly late-time-accelerated expansion. So, this new term may be added to the gravitational actions of f(T )-gravity.